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Yang, Haiyu, Haiyu Song, Wei Li, Kexin Qin, Haoyu Shi, and Qi Jiao. "Social Image Annotation Based on Image Captioning." WSEAS TRANSACTIONS ON SIGNAL PROCESSING 18 (May 19, 2022): 109–15. http://dx.doi.org/10.37394/232014.2022.18.15.
Повний текст джерелаАнотація:
With the popularity of new social media, automatic image annotation (AIA) has been an active research topic due to its great importance in image retrieval, understanding, and management. Despite their relative success, most of annotation models suffer from the low-level visual representation and semantic gap. To address the above shortcomings, we propose a novel annotation method utilizing textual feature generated by image captioning, in contrast to all previous methods that use visual feature as image feature. In our method, each image is regarded as a label-vector of k userprovided textual tags rather than a visual vector. We summarize our method as follows. First, the image visual features are extracted by combining the deep residual network and the object detection model, which are encoded and decoded by the mesh-connected Transformer network model. Then, the textual modal feature vector of the image is constructed by removing stop-words and retaining high-frequency tags. Finally, the textual feature vector of the image is applied to the propagation annotation model to generate a high-quality image annotation labels. Experimental results conducted on standard MS-COCO datasets demonstrate that the proposed method significantly outperforms existing classical models, mainly benefiting from the proposed textual feature generated by image captioning technology.
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Trajković, Jovana. "SOCIAL MEDIA AND BODY IMAGE." MEDIA STUDIES AND APPLIED ETHICS 3, no. 2 (November 29, 2022): 87–96. http://dx.doi.org/10.46630/msae.2.2022.07.
Повний текст джерелаАнотація:
Abstract: Social media is a communication channel that is becoming increasingly widespread. Its impact on people is gaining significance. Numerous studies have shown that social media activity can negatively affect people’s emotional states. The aim of this paper is to review the literature to examine the influence of social media on body image, which is viewed as the perception of one’s own body and the feelings and thoughts associated with it. Research review suggests that Facebook and Instagram use is associated with greater body image dissatisfaction. However, as the use of social media is not homogeneous and not all users are exposed to the same content, a more nuanced approach to measuring its use is required. If an individual follows physical appearance-based accounts on social networking platforms, their home pages will be filled with idealized representations of a human body, leading to more intense and frequent comparisons with other people. Such use unmistakably leads to negative body image, and the solution that stands out is education in media literacy which should develop critical and analytical skills in people. Keywords: body image, media, social networks, Facebook, Instagram
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Noviyanti, Nur Irma. "Instagram Social Media As Guidance And Counseling Media Based On Technology." International Journal of Applied Guidance and Counseling 1, no. 1 (February 6, 2020): 16–19. http://dx.doi.org/10.26486/ijagc.v1i1.1045.
Повний текст джерелаАнотація:
one of the most important counselor tasks to response industrial revolution 4.0 is guidance and counselingservice using new innovation, suchus social-media. Internet user Indonesia are 64,8 % from all citizen, with user duration using social-media 3-4 hours each day. Social media acess is the second priority after using communication needed. Instagram is the second social-media with high access by user after facebook. Instagram is one of social-media application to share text, image, or video. This work is gained to analyse that instagram could be used by counselor as media to do guidance and counseling service based on technology. There are many fiture such us image upload, video, caption, comment, hashtags, instagram story, instagram live, direct message and highlight could be used by counselor.
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Y. El-mashad, Shady, Amani M. Yassen, Abdulwahab K. Alsammak, and Basem M. Elhalawany. "Local Features-Based Watermarking for Image Security in Social Media." Computers, Materials & Continua 69, no. 3 (2021): 3857–70. http://dx.doi.org/10.32604/cmc.2021.018660.
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Xu, Bin, Guoliang Fan, and Dan Yang. "Topic Modeling Based Image Clustering by Events in Social Media." Scientific Programming 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/5283471.
Повний текст джерелаАнотація:
Social event detection in large photo collections is very challenging and multimodal clustering is an effective methodology to deal with the problem. Geographic information is important in event detection. This paper proposed a topic model based approach to estimate the missing geographic information for photos. The approach utilizes a supervised multimodal topic model to estimate the joint distribution of time, geographic, content, and attached textual information. Then we annotate the missing geographic photos with a predicted geographic coordinate. Experimental results indicate that the clustering performance improved by annotated geographic information.
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Yan, Keyu. "The Impact of Social Media on Corporate Social Responsibility: Motivations, Practices, and Outcomes." Advances in Economics, Management and Political Sciences 162, no. 1 (January 10, 2025): 119–24. https://doi.org/10.54254/2754-1169/2025.20366.
Повний текст джерелаАнотація:
In the information age, the rapid development of social media has influenced the public's views and cognition, and has directly and indirectly increased the expectations for companies to fulfill their social responsibilities. Based on a review of previous research literature, this paper argues that the impact of social media on corporate social responsibility (CSR) primarily includes motivational, operational, and effect-based impacts. The motivational impact of social media on CSR can be attributed to four factors: meeting consumer expectations and shaping brand image, reducing the pressure from social media public opinion, gaining interactive incentives from social media, and providing a transparent communication platform to capture stakeholders' attention. Social media also affects the specific practices of companies in implementing CSR activities. It offers a more effective platform for disseminating CSR information, helps establish appropriate communication methods, and enhances CSR image management on social media. Fulfilling CSR through social media can yield positive outcomes, shape corporate reputation and brand image, actively influence consumer attitudes and behaviors, and encourage companies to fulfill their social responsibilities in alignment with publicized information. Future research could focus on the differing impacts of social media on companies of various types and sizes, providing more detailed guidance and recommendations for companies.
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Shahria, M. M., Mohammed Nazim Uddin, and Miraj Ahmed. "Social Media Security: Identity Theft Prevention." Volume 5 - 2020, Issue 8 - August 5, no. 8 (September 16, 2020): 1656–62. http://dx.doi.org/10.38124/ijisrt20aug762.
Повний текст джерелаАнотація:
Social networking sites are becoming parts and parcels of our daily life. With the increasing of its popularity, the cybercrimes, targeting these platforms are also increasing. Cybercriminals use this platform to harass the victims personally, socially and financially. Such type of crimes is performed using some of the vulnerabilities of the social networking platforms. Identity theft is one of those crimes which is increasing alarmingly. By creating a fake account, using the same information and profile picture, one can easily take disguise of another person. Hence, the criminal can chat with other persons impersonating the victim. Thus, the criminal takes the disguise of a person and starts harassing other people. The consequence of this problem is very dangerous. By doing so, the criminal ruins the image of the victim. There are so many cases where victims attempted to commit suicide after facing this type of terrible problem. All these things are occurring as the criminal can download or collect the profile picture of the victim easily and open a clone account easily. The availability of information is giving the chance to the cybercriminal to make an account exactly looks like the victim’s one. In this paper, we attempt to prevent this type of identity theft by an image based solution on the social networking platforms. The name of this model is ‘Image Based Identity Theft Prevention’.
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Juntao Zhao, Juntao Zhao. "Multichannel Fusion Based on modified CNN for Image Emotion Recognition." 電腦學刊 33, no. 1 (February 2022): 013–19. http://dx.doi.org/10.53106/199115992022023301002.
Повний текст джерелаАнотація:
<p>Social media networks are an integral part of people’s daily life. Users share images and texts to express their emotions and opinions. Analyzing the image and text content published by these users can help understand and predict user behavior, so as to carry out marketing, public opinion monitoring and personalized recommendation. Weibo, Wechat and other social media are important ways of self-expression. Images are more intuitive than text. Therefore, more scholars begin to pay attention to the research of image emotion analysis. At present, image emotion analysis methods pay seldom attention to the influence of saliency object and face on image emotion expression. Therefore, we propose a multichannel fusion method based on modified CNN for image emotion recognition. Firstly, saliency target and face target region are detected in the whole image. Then feature pyramid is used to improve CNN to recognize saliency target emotion. Weighted loss CNN emotion recognition is constructed on multi-layer supervision module. Finally, the saliency target emotion, face target emotion and the directly recognized emotion on the whole image are fused to get the final result of emotion classification. Experimental results show that the proposed method can improve the accuracy of image emotion recognition.</p> <p> </p>
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Vosoughi Motlagh, Afsaneh, Sara Kamjou, and Jalil Etemaad. "Predicting Body Image Concerns, Social Isolation, and Mood by the Amount of Social Media Addiction." Practice in Clinical Psychology 11, no. 4 (April 1, 2023): 0. http://dx.doi.org/10.32598/jpcp.11.4.856.1.
Повний текст джерелаАнотація:
Objective: The use of the Internet is widely increasing among the new generation, shaping an important aspect of people's lives. The use of the social media can influence body image concerns, social isolation, and social mood. The purpose of the present study is to assess body image concerns, social isolation, and mood based on the amount of social media use. Method: This study has been conducted using a descriptive method in the form of correlation. The study population was all people aged between 20 and 40 in Shiraz, among which 311 people (191 women and 119 men) has been selected by the convenience sampling method. The tools used in this study were body image concerns Inventory (BICI, 2005), Social Isolation Assessment Standard Questionnaire (SIASI, 2013), Positive and Negative Affect Schedule (PANAS, 1988), and social media addiction scale (SMAS_AF, 2017). Correlation coefficients (using the SPSS software) and structural equation modeling analysis (using AMOS statistical software) were employed to investigate the variables of social isolation prediction model. Results: The results of the study showed that mood (β=0.15, p=0.007) and use of social media (β=0.19, p=0.0001) can predict social isolation with the mediating role of body image concerns(β=0.18, p=0.001). The results showed that the mood and use of social media can predict social isolation both directly and with the mediation of body image concern. Conclusion: Based on the results of this study, mood and use of social media can predict social isolation with the mediating role of body image concerns. Negative mood can make people sensitive to their body image. People have a distorted perception of their body image and this concern leads to social isolation.
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Van Dyk, Anja, Elmarie Slabbert, and Aaron Tkaczynski. "Segmenting Tourists Based on Traditional Versus Social Media Usage and Destination Image Perception." Tourism Culture & Communication 20, no. 4 (October 30, 2020): 189–206. http://dx.doi.org/10.3727/194341420x15905692660247.
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Despite considerable insight into both traditional and social media, the research on these media types is largely mutually exclusive. Consequently, it is largely not known what media tourists use before forming an image of a destination for potential visitation. To provide insight into this phenomena, this study segmented 558 tourists to South Africa based on their media usage and destination image perception. The first segment, experienced South African tourists (39%), did not use media when forming an image of South Africa, but rather focused on their frequent past experience. This segment rated cognitive and behavioral image of South Africa the highest. The second segment, friends and family orientated tourists (21%), utilized personal sources in their destination image formation of South Africa. They also rated the country's image the lowest. The third segment, multiple media usage tourists (40%), employed both traditional and social media in forming their destination image of South Africa. These tourists also rated affective image of the country the highest. While destination marketing organizations (DMOs) need to continue to employ traditional and social media to cater for different consumer learning techniques and different consumer response stages of the largest segment (multiple media usage segments), three fifths of the sample are currently being neglected. Because past experience is incredibly relevant for segment validation and representing destination image of the two smaller segments, the DMO needs to identify through in-depth interviews what South Africa's destination image means to all three segments. This process allows comparisons between the segments to be made. It can identify how these tourists' perception of the country's image has changed with experience and if their perceived image accurately represents what is currently marketed by DMOs.
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Dundua, Tamar. "English as a Social Media Lingua Franca among Georgian Social Media Users." International Journal of Linguistics, Literature and Translation 6, no. 4 (April 28, 2023): 136–40. http://dx.doi.org/10.32996/ijllt.2023.6.4.18.
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The present article examines the status of English as a social media Lingua Franca based on Georgian social media users. The purpose of the research is to identify how dominant and frequent the usage of English is on social media in Georgia. It also includes the respondents’ attitude towards the change, their readiness to accept it and their proper understanding of the neologisms established on social media. The article also includes a diachronic overview of the dominance of different languages in the Georgian language. In order to obtain the current linguistic image on social media, descriptive research was conducted, and the data was collected and processed based on the answers on the Google form questionnaire, which included 15 questions. In the light of the descriptive study, it was apparent that the majority of the respondents (197) agree that English is the main language for communication apart from the native language.
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Wang, Yaxiong, Li Zhu, and Xueming Qian. "Social image retrieval based on topic diversity." Multimedia Tools and Applications 80, no. 8 (January 11, 2021): 12367–87. http://dx.doi.org/10.1007/s11042-020-10221-z.
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AbstractImage search re-ranking is one of the most important approaches to enhance the text-based image search results. Extensive efforts have been dedicated to improve the accuracy and diversity of tag-based image retrieval. However, how to make the top-ranked results relevant and diverse is still a challenging problem. In this paper, we propose a novel method to diversify the retrieval results by latent topic analysis. We first employ NMF (Non-negative Matrix Factorization) Lee and Seung (Nature 401(6755):788–791, 1999) to estimate the initial relevance score to the query q. Then, the initial relevance score is fed into an adaptive multi-feature fusion model to learn the final relevance score. Next, the diversification process is conducted. We group all the images by semantic clustering and estimate the topic distribution of each cluster by topic analysis. The clusters are ranked based on the topic distribution vector and the final retrieval image list is obtained by a greedy selection mechanism based on the estimated relevances. Experimental results on the NUS-Wide dataset show the effectiveness of the proposed approach.
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Qian, Xueming, Mingdi Li, Yayun Ren, and Shuhui Jiang. "Social media based event summarization by user–text–image co-clustering." Knowledge-Based Systems 164 (January 2019): 107–21. http://dx.doi.org/10.1016/j.knosys.2018.10.028.
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Himani Jain. "Multilayer Perceptron’s Neural Network Based Image Spam Detection on Social Media." Journal of Electrical Systems 20, no. 7s (May 4, 2024): 2586–603. http://dx.doi.org/10.52783/jes.4092.
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Spam, typically unwanted material, can manifest in various forms, including images. While numerous machine learning techniques excel in detecting textual spam, they often falter when it comes to identifying image-based spam. This paper introduces a novel framework designed specifically for identifying image spams. Images are categorized into two groups: spam images, containing undesirable material, and ham images, encompassing everything else. In this paper, a novel technique based on CNN and gated recurrent unit (GRU) for image spam detection has been proposed. Our proposed methodology hinges on the utilization of diverse pre-trained deep learning models, such as InceptionV3, DenseNet121 (Densely Connected Convolutional Networks 121), ResNet50 (Residual Networks), VGG16 (Visual Geometry Group), and MobileNetV2, to effectively filter out unwanted spam images. We evaluate the performance of our approach using different Dataset. Additionally, we address the challenge of limited labeled data by leveraging transfer learning and employing data augmentation techniques. Experimental results demonstrate the efficacy of our proposed model, achieving impressive accuracy levels while maintaining computational efficiency, with testing times ranging from one to two seconds for the challenge dataset.
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Zarezadeh, Zohreh (Zara), and Ulrike Gretzel. "Iranian Heritage Sites on Social Media." Tourism Analysis 25, no. 2 (July 8, 2020): 345–57. http://dx.doi.org/10.3727/108354220x15758301241855.
Повний текст джерелаАнотація:
International heritage tourism is the backbone of Iranian tourism. To positively influence the country's destination image and attract more international tourists, World Heritage sites (WHSs) need to be present on social media. This article investigates the representation of Iranian WHSs on social media based on a content analysis of WHS-related Facebook, Instagram, and TripAdvisor pages. The findings of the study indicate that social media marketing by Iranian WHSs is in its infancy. Iranian WHS information currently available on the three social media platforms is incomplete, confusing, and mostly provided by other stakeholders, leading to weak and diffused WHS brands that contribute little to a positive destination image. The article thus argues that WHSs in Iran need to urgently recognize the importance of social media for reaching international tourists and need to overcome their organizational limitations.
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Sirmayanti, Sirmayanti, Mahjud I, Puspita I, Mahyati M, Rizal M, Hasanah U, Mujahida N, et al. "Youth Creativity Media Empowerment Through Social Media Content Creator." International Journal Of Community Service 2, no. 4 (November 20, 2022): 421–26. http://dx.doi.org/10.51601/ijcs.v2i4.144.
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Generations of Millennial, X, Y and Z are very synonymous with social media presence. More focus on Generation Z which in fact were born in an era that is surrounded by cyberspace with Internet facilities, cellular technology and digital technology that are connected stable. PKM partners are students of MAN 3 Makassar and GMA-community to carry out optimization of science and technology applications through content creators with social media platforms so that Islamic da'wah media is more widespread and affordable to all people. The main target of partners is the digital natives of the Gen-Z. They are the GMA-community Mosque Youth Association which their number are 30% of the community population. The types of PKM activities are learning-by-project-based training and coaching graphic design & video-image editing to target partners so that new skills are formed in the creativity of da'wah content on the created social media platforms. The results of the technology transfer that have been provided are content creator training and the creation of 5 YouTube, Instagram, Facebook, Spotify and Web media accounts equipped as account administrator for managing social media and image and video products of the Islamic da'wah content.
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Farkas, Xénia, and Márton Bene. "Images, Politicians, and Social Media: Patterns and Effects of Politicians’ Image-Based Political Communication Strategies on Social Media." International Journal of Press/Politics 26, no. 1 (September 21, 2020): 119–42. http://dx.doi.org/10.1177/1940161220959553.
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Although images have always been part of politics, research on the visual aspects of political communication recently gained momentum, especially with the spread of social media–based political communication. However, there are still several significant research gaps in this field. The aim of this article is to identify and compare the patterns and effects of Hungarian politicians’ ( n = 51) image-based communication on Facebook ( n = 2,992) and Instagram ( n = 868) during the Hungarian parliamentary election campaign in 2018. By doing so, we shed light on two important dimensions of personalization: individualization and privatization. This work is designed to fill three gaps in the literature. We argue that existing research of visual political communication (1) treats images predominantly as illustrations, (2) is limited to single-platform studies, and (3) does not investigate the engagement effects of images. To move beyond these limitations, this study investigates images as objects of interest on their own; it adopts a cross-platform comparative approach and examines the engagement effects of visual cues by applying a combination of inductive and deductive qualitative content analysis. Our results show that images are often used to personalize communication. While on Facebook the individualization dimension of personalization is more common and popular, on Instagram its privatization dimension prevails. Furthermore, on Facebook, users like more politics-related candidate-centered images, but on Instagram we could not find similar effects for more informal visuals.
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Zampoglou, Markos, Symeon Papadopoulos, Yiannis Kompatsiaris, Ruben Bouwmeester, and Jochen Spangenberg. "Web and Social Media Image Forensics for News Professionals." Proceedings of the International AAAI Conference on Web and Social Media 10, no. 2 (August 4, 2021): 159–66. http://dx.doi.org/10.1609/icwsm.v10i2.14845.
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User-generated content -commonly referred to as "eyewitness media"- has become an essential component in journalism and news reporting. Increasingly more news providers, such as news agencies, broadcasters and Web-only players have set up teams of dedicated investigators or are in the process of training parts of their journalistic workforce to gather and evaluate material from social networks and the Web. If verified, such content can be invaluable in delivering a news story. However, while source checking and verification is as old as journalism itself, the verification of digital material is a relatively young field, with protocols and assisting tools still being developed. In this work, we present our efforts towards a Web-based image verification platform. The platform, currently in its alpha stage, features image tampering detection using a number of state-of-the-art algorithms and image metadata visualization. We discuss the current strengths and limitations of the platform and the implemented state-of-the-art with respect to the specific requirements of the task, resulting from its Web-based nature and its intended use by news investigators with limited expertise in the domain of image forensics.
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Azam, Samiul, and Marina L. Gavrilova. "Biometric Pattern Recognition from Social Media Aesthetics." International Journal of Cognitive Informatics and Natural Intelligence 11, no. 3 (July 2017): 1–16. http://dx.doi.org/10.4018/ijcini.2017070101.
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Online social media (OSN) has witnessed a significant growth over past decade. Millions of people now share their thoughts, emotions, preferences, opinions and aesthetic information in the form of images, videos, music, texts, blogs and emoticons. Recently, due to existence of person specific traits in media data, researchers started to investigate such traits with the goal of biometric pattern analysis and recognition. Until now, gender recognition from image aesthetics has not been explored in the biometric community. In this paper, the authors present an authentic model for gender recognition, based on the discriminating visual features found in user favorite images. They validate the model on a publicly shared database consisting of 24,000 images provided by 120 Flickr (image based OSN) users. The authors propose the method based on the mixture of experts model to estimate the discriminating hyperplane from 56 dimensional aesthetic feature space. The experts are based on k-nearest neighbor, support vector machine and decision tree methods. To improve the model accuracy, they apply a systematic feature selection using statistical two sampled t-test. Moreover, the authors provide statistical feature analysis with graph visualization to show discriminating behavior between male and female for each feature. The proposed method achieves 77% accuracy in predicting gender, which is 5% better than recently reported results.
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Niu, Xinghui, Yueyan Li, and Mingzhe Gao. "Social Media Use and Regional Image Perception: An Empirical Study Based on the Gansu Image Perception Questionnaire Survey." International Journal of Education, Humanities and Social Sciences 1, no. 1 (October 23, 2024): 52–60. http://dx.doi.org/10.70088/xnxe5p04.
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This study, using Gansu Province in China as a case, explores the impact of social media use on regional image perception. It finds that social media enhances users' perceptions of economic, political, cultural, and environmental images, indirectly increasing their satisfaction with the Gansu region. The research shows that social media plays a positive role in constructing regional images, particularly through user-generated content on short video platforms, which is more attractive and shareable. Among these, environmental and cultural images have the most significant impact on regional image compared to economic and political images. Therefore, it is recommended that regional governance bodies shift their promotional strategies to stimulate internet users' creative enthusiasm to improve the effectiveness of regional image dissemination.
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Zhang, Jing, Ying Yang, Qi Tian, Li Zhuo, and Xin Liu. "Personalized Social Image Recommendation Method Based on User-Image-Tag Model." IEEE Transactions on Multimedia 19, no. 11 (November 2017): 2439–49. http://dx.doi.org/10.1109/tmm.2017.2701641.
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Kostyk, Alena, and Bruce A. Huhmann. "Perfect social media image posts: symmetry and contrast influence consumer response." European Journal of Marketing 55, no. 6 (February 4, 2021): 1747–79. http://dx.doi.org/10.1108/ejm-09-2018-0629.
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Purpose Two studies investigate how different structural properties of images – symmetry (vertical and horizontal) and image contrast – affect social media marketing outcomes of consumer liking and engagement. Design/methodology/approach In Study 1’s experiment, 361 participants responded to social media marketing images that varied in vertical or horizontal symmetry and level of image contrast. Study 2 analyzes field data on 610 Instagram posts. Findings Study 1 demonstrates that vertical or horizontal symmetry and high image contrast increase consumer liking of social media marketing images, and that processing fluency and aesthetic response mediate these relationships. Study 2 reveals that symmetry and high image contrast improve consumer engagement on social media (number of “likes” and comments). Research limitations/implications These studies extend theory regarding processing fluency’s and aesthetic response’s roles in consumer outcomes within social media marketing. Image posts’ structural properties affect processing fluency and aesthetic response without altering brand information or advertising content. Practical implications Because consumer liking of marketing communications (e.g. social media posts) predicts persuasion and sales, results should help marketers design more effective posts and achieve brand-building and behavioral objectives. Based on the results, marketers are urged to consider the processing fluency and aesthetic response associated with any image developed for social media marketing. Originality/value Addressing the lack of empirical investigations in the existing literature, the reported studies demonstrate that effects of symmetry and image contrast in generating liking are driven by processing fluency and aesthetic response. Additionally, these studies establish novel effects of images’ structural properties on consumer engagement with brand-based social media marketing communications.
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Maresova, Petra, Jan Hruska, and Kamil Kuca. "Social Media University Branding." Education Sciences 10, no. 3 (March 16, 2020): 74. http://dx.doi.org/10.3390/educsci10030074.
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Globalization has increased the demands placed on higher education and increased competition among universities. In response, institutions of higher education have started to consider their online presence as a potential competitive advantage. The aim of this article is to analyze and compare Facebook activity and content created by the world’s top ten universities. The professional social media analytics tool Socialbakers is used to monitor activity and collect data for analysis. The world’s top ten universities are determined based on the Quacquarelli Symonds (QS) University Rankings. The study results are divided into four categories: an analysis of the number of fans, of content, of style, and of post promotion. All of the studied universities upload a post at least once per day. Based on the study results, selected posts could be examples of best practice and serve to inspire other educational institutions to improve their brand image and communication on social networks. Social media provide a large amount of detailed data concerning the behavior of students and other stakeholders and on the effectiveness of promotional campaigns. To use social media effectively, it is necessary to collect the available data and evaluate them to gain insight on which to base an appropriate social media strategy
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Gawade, Prema Pandurang, and Sarang Achyut Joshi. "Persona Identification based on Social Media Profile Images for Personification and Safety." Webology 19, no. 1 (January 20, 2022): 1297–314. http://dx.doi.org/10.14704/web/v19i1/web19087.
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Personification is important to ensure safety in social media. Images embedded in social media data is an important source intelligently ensure the personal safety. Paper proposes an applied machine learning on embedded image media to extract important feature traits and understand the semantics of correlation of feature space to understand the personification of given user. A strong belief is calculated using cascaded method and this inference is applied to different ml algorithms to derive the overlap of feature space. This algorithm validates the proposed objective that the user with more overlap and correlation among feature space are highly personified with each other. Using this personification-based method, better safety is ensured to mitigate possible social media attacks.
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Sabuncu, İbrahim, Berivan Edeş, Doruk Sıtkıbütün, İlayda Girgin, and Kadir Zehir. "Creating Brand Image Profile by Social Media Analysis." EMAJ: Emerging Markets Journal 11, no. 2 (December 13, 2021): 8–15. http://dx.doi.org/10.5195/emaj.2021.228.
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The purpose of creating a brand image profile is to measure the brand perception of consumers considering brand attributes. Thus, marketing decisions can be made based on the brand's strengths and weaknesses by determining them. The brand image profile is traditionally created using the attitude scales and surveys. However, alternative methods are needed since the questionnaires' responses are careless, the number of participants is relatively low and the cost per participant is high. In this study, as an alternative method, creating a brand image profile by analyzing social media data with artificial intelligence was made for the iPhone product. Firstly, the focus group study determined the attributes related to the last version of the iPhone. Then, between December 17th, 2019 and March 23rd, 2020, 87.227 tweets that include these attributes in English were collected from the Twitter social media platform through the RapidMiner data mining tool. Sentiment analysis was performed on collected tweets by the MeaningCloud text mining tool. In this analysis, positive and negative emotions were tried to be detected through artificial intelligence algorithms. Net Brand Reputation Score (NBR) was calculated using the positive and negative tweets amount for each attribute separately. Brand image profile was created by skew analysis using NBR values. As a result, it is thought that social media analysis can be a complementary method that can be used with traditional methods in creating a brand image profile. So, it is seen as an inevitable method to use in further studies to make sentiment analysis by processing raw data received from the Social Media platforms through artificial intelligence algorithms to transform the product label or the perspectives of an event into meaningful information.
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Wang, Yuping, Fatemeh Tahmasbi, Jeremy Blackburn, Barry Bradlyn, Emiliano De Cristofaro, David Magerman, Savvas Zannettou, and Gianluca Stringhini. "Understanding the Use of Fauxtography on Social Media." Proceedings of the International AAAI Conference on Web and Social Media 15 (May 22, 2021): 776–86. http://dx.doi.org/10.1609/icwsm.v15i1.18102.
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Despite the influence that image-based communication has on online discourse, the role played by images in disinformation is still not well understood. In this paper, we present the first large-scale study of fauxtography, analyzing the use of manipulated or misleading images in news discussion on online communities. First, we develop a computational pipeline geared to detect fauxtography, and identify over 61k instances of fauxtography discussed on Twitter, 4chan, and Reddit. Then, we study how posting fauxtography affects engagement of posts on social media, finding that posts containing it receive more interactions in the form of re-shares, likes, and comments. Finally, we show that fauxtography images are often turned into memes by Web communities. Our findings show that effective mitigation against disinformation need to take images into account, and highlight a number of challenges in dealing with image-based disinformation.
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Niu, Xiaomei. "Interactive 3D reconstruction method of fuzzy static images in social media." Journal of Intelligent Systems 31, no. 1 (January 1, 2022): 806–16. http://dx.doi.org/10.1515/jisys-2022-0049.
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Abstract Because the traditional social media fuzzy static image interactive three-dimensional (3D) reconstruction method has the problem of poor reconstruction completeness and long reconstruction time, the social media fuzzy static image interactive 3D reconstruction method is proposed. For preprocessing the fuzzy static image of social media, the Harris corner detection method is used to extract the feature points of the preprocessed fuzzy static image of social media. According to the extraction results, the parameter estimation algorithm of contrast divergence is used to learn the restricted Boltzmann machine (RBM) network model, and the RBM network model is divided into input, output, and hidden layers. By combining the RBM-based joint dictionary learning method and a sparse representation model, an interactive 3D reconstruction of fuzzy static images in social media is achieved. Experimental results based on the CAD software show that the proposed method has a reconstruction completeness of above 95% and the reconstruction time is less than 15 s, improving the completeness and efficiency of the reconstruction, effectively reconstructing the fuzzy static images in social media, and increasing the sense of reality of social media images.
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Savitri, Citra, Ratih Hurriyati, Lili Adi Wibowo, and Heny Hendrayati. "The role of social media marketing and brand image on smartphone purchase intention." International Journal of Data and Network Science 6, no. 1 (2022): 185–92. http://dx.doi.org/10.5267/j.ijdns.2021.9.009.
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The purpose of this study was to analyze the relationship between Social Media Marketing and Brand Image, Social Media Marketing relationship and Purchase Intention, Brand Image Relationship and Purchase Intention and finally, the relationship between Social Media Marketing and Purchase Intention through Brand Image. The approach in the research used is a quantitative approach using PLS-SEM SmartPLS software as a data processing tool. In this study, the data collection technique was carried out using a questionnaire or online questionnaire which was distributed to 234 respondents of Millennial Smartphone Consumers in Banten Indonesia. Sampling system was accomplished with a snowball sampling method. Based on the results of hypothesis testing, it was found that there was a positive and significant relationship between Brand Image (BRI) and Purchase Intention. There was also a positive and significant relationship between Social Media Marketing and Brand Image. However, there was an insignificant relationship between Social Media Marketing and Brand Image while there was a significant relationship between Social Media Marketing and Purchase Intention through Brand Image as Mediator.
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Yani, Nurhayani, Gufa Rinata Gufa, Gugup Tugi Prihatma Gugup, and Irwan Zaini Irwan. "Pengaruh Brand Ambassador (Twice) Dan Brand Image Terhadap Minat Beli Produk Scarlett Whitening Pada Media Sosial Instagram." Jurnal Manajemen Perusahaan: JUMPA 2, no. 2 (September 2, 2023): 1–9. http://dx.doi.org/10.30656/jumpa.v2i2.7188.
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This background of this research is based on the problems that occured to Scarlett Whitening on Instagram social media relared to the brand ambassador (Twice) and brand image of Scarlett Whitening products in detail. So, the research questions are as follows : (1) Does Twice’s Brand Ambassador affect the Buying Interest of Scarlett Whitening Products on Instagram Sosial Media (2) Does Brand Image affect Buying Interest of Scarlett Whitening product on Instagram Social Media (3) Does Twice’s Brand Ambassador and Brand Image together influence the Buying Interest of Scarlett Whitening product on Instagram Social Media. The Research sample is 55 respondents or consumers of Scarlett Whitening product who use Instagram. The results in this study indicate the influence of the Brand Ambassador variable on the Scarlett Whitening product on Instagram Social Media, Brand Image on the Scarlett Whitening product on Instagram Social Media. This is based on the t-test through the SPSS V.25 program.
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Reddy, M. Prashanth, and Dr S. Suneetha. "FACTORS INFLUENCING BRAND AWARNESS AND BRAND IMAGE ON SOCIAL MEDIA PLATFORM." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 01 (January 15, 2024): 1–6. http://dx.doi.org/10.55041/ijsrem28135.
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The many facets of what influences the growth of brand awareness and brand image on social media platforms are examined in this study. Social media has emerged as a crucial platform for customer engagement and brand promotion in today's digital world. For marketers looking to build and maintain a strong online presence, it is imperative that they comprehend the intricacies of brand perception in this setting. Based on an extensive analysis of existing literature and practical investigations, this abstract identifies the primary determinants of brand recognition and image on social media. Elements such as brand attributes, pricing strategy, EWOM & Promotional activities creates Brand Awareness & Being Reliable in proving products and services , brands reputation result into Brand Image on social Media. Key words: Brand Awareness, Brand Image, Social Media Platforms, Target Audience, Online Presence
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Narayana Rao, T. Venkat, and Somasani Jyothi. "Content Based Image Retrieval Based on Shape, Color and Structure of the Image." International Journal on Recent and Innovation Trends in Computing and Communication 7, no. 3 (March 27, 2019): 48–53. http://dx.doi.org/10.17762/ijritcc.v7i3.5264.
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In the recent era, as technology is growing rapidly the usage of social media is also increasing as a result large databases are required for storing the images. With the advancements in the technology, the storage of these images in computers has become possible. But retrieving the images is becoming a big task. We need to store them in a sequential manner and retrieve them when required. This paper details retrieval of images by considering the features related to content like shape, color, texture is called CBIR (content based image retrieval). As it is very difficult to extract the pictures in such huge data bases so we chose this technique which aim at high efficiency.
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Li, Zilong, Yong Zhou, and Hongdong Wang. "Social media image classification and retrieval method based on deep hash algorithm." International Journal of Web Based Communities 18, no. 3/4 (2022): 276. http://dx.doi.org/10.1504/ijwbc.2022.125506.
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Wang, Hongdong, Yong Zhou, and Zilong Li. "Social media image classification and retrieval method based on deep hash algorithm." International Journal of Web Based Communities 18, no. 3/4 (2022): 1. http://dx.doi.org/10.1504/ijwbc.2022.10047487.
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杨, 靖. "Image-Text Sentiment Analysis Method in Social Media Domain Based on ViLT." Operations Research and Fuzziology 13, no. 06 (2023): 7346–58. http://dx.doi.org/10.12677/orf.2023.136722.
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Jia, Zhaohao. "Psychological Analysis of Social Media Visual Content Based on Image Recognition Algorithm." International Journal of Electrical and Electronics Engineering 11, no. 9 (September 30, 2024): 196–204. http://dx.doi.org/10.14445/23488379/ijeee-v11i9p117.
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Dane, Alexandra, and Komal Bhatia. "The social media diet: A scoping review to investigate the association between social media, body image and eating disorders amongst young people." PLOS Global Public Health 3, no. 3 (March 22, 2023): e0001091. http://dx.doi.org/10.1371/journal.pgph.0001091.
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Background Eating disorders are a group of heterogenous, disabling and deadly psychiatric illnesses with a plethora of associated health consequences. Exploratory research suggests that social media usage may be triggering body image concerns and heightening eating disorder pathology amongst young people, but the topic is under-researched as a global public health issue. Aim To systematically map out and critically review the existing global literature on the relationship between social media usage, body image and eating disorders in young people aged 10–24 years. Methods A systematic search of MEDLINE, PyscINFO and Web of Science for research on social media use and body image concerns / disordered eating outcomes published between January 2016 and July 2021. Results on exposures (social media usage), outcomes (body image, eating disorders, disordered eating), mediators and moderators were synthesised using an integrated theoretical framework of the influence of internet use on body image concerns and eating pathology. Results Evidence from 50 studies in 17 countries indicates that social media usage leads to body image concerns, eating disorders/disordered eating and poor mental health via the mediating pathways of social comparison, thin / fit ideal internalisation, and self-objectification. Specific exposures (social media trends, pro-eating disorder content, appearance focused platforms and investment in photos) and moderators (high BMI, female gender, and pre-existing body image concerns) strengthen the relationship, while other moderators (high social media literacy and body appreciation) are protective, hinting at a ‘self-perpetuating cycle of risk’. Conclusion Social media usage is a plausible risk factor for the development of eating disorders. Research from Asia suggests that the association is not unique to traditionally western cultures. Based on scale of social media usage amongst young people, this issue is worthy of attention as an emerging global public health issue.
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Iskamto, Dedi, and Adryan Edhie Wicaksono. "Computational Architecture of Digital Marketing of Toyota Corporation." Jurnal Penelitian Pendidikan IPA 9, SpecialIssue (December 25, 2023): 1249–53. http://dx.doi.org/10.29303/jppipa.v9ispecialissue.7233.
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Toyota uses social media marketing strategies Instagram to promote its products and include important information about the automotive industry to influence social media marketing, e-wom, brand image, brand trust, and purchase intention. The research aims to determine the influence of Toyota's social media marketing, brand image, brand trust, and purchase intention. The sample taken in this research was 385 respondents using quantitative methods and data analysis techniques using SmartPLS. Based on the results of the analysis it was found that Social Media Marketing has a significant and positive effect on Purchase Intention, Social Media Marketing has a significant and positive effect on Brand Trust, Social Media Marketing has a significant and positive effect on the Brand Image, Brand Trust has a significant and positive effect on Purchase Intention, Brand Image has a significant and positive effect on Purchase Intention, E-Wom moderate Social Media Marketing has a significant and positive effect on Purchase Intention at Toyota
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Koronczai, B., and Z. Demetrovics. "The association between social media use and mental health among adolescents and young adults." European Psychiatry 65, S1 (June 2022): S126. http://dx.doi.org/10.1192/j.eurpsy.2022.347.
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Introduction The associations of problematic social media use, the special use of image-based social media (photo editing, following celebrities) and mental health (body dissatisfaction, self-esteem, depression) have been established (e.g. Yurdagül et al., 2019; Gioia, Griffiths, Boursier, 2020; Lowe-Calverley and Grieve, 2021). The links may be explained with the theory of social comparison and self-objectification. Objectives Testing theory-oriented hypotheses related to image-based social media use and body dissatisfaction, gender specifically, among adolescents and young adults. Methods Three surveys have been conducted with convenience sampling: (1) 117 Hungarian university students in person (mean age=22.4, SD=2.9, 79% female), (2) 383 high school students in person (mean age=16.5, SD=1.2, 58% female); (3) 124 Israeli adolescents online (mean age=16.8, SD=2.7, 68% female). Results (1): The tendency of modifying body image in social media (the frequency of modifying pictures, the use of filters) mediates the association between body shame and problematic social media use. Physical appearance social comparison mediates the association between self-related negative emotions and attitude (low self-esteem+ineffectiveness) and problematic social media use. (2): The technology-based social comparison mediate the association between muscle checking and problematic Instagram use among boys. (3) Physical appearance social comparison mediates the association between the frequency of following celebrities and body dissatisfaction among girls, but not among boys. Conclusions During the use of image based social media, social comparison and the exposure to the beauty standards may lead to poorer mental health, which could result in problematic social media use as maladaptive coping. Disclosure No significant relationships.
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Xia, Dongmei, Pengfei Zhao, Ji Wang, and Yingji Li. "The projection of Chinese University online image and social media engagement based on Bayesian model." PLOS ONE 19, no. 4 (April 16, 2024): e0300625. http://dx.doi.org/10.1371/journal.pone.0300625.
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Social media platforms provide the public with a forum for interaction and communication with tourism destinations, playing a significant role in the shaping and dissemination of destination images. Similarly, social media plays a vital role in the construction and propagation of online images for higher education institutions. For instance, indicators such as likes, shares, and visits on Weibo can serve as measures of public engagement with university social media. To reveal the triggering rules of social media engagement by projected images of destinations and related factors, this paper builds a Bayesian model using data from posts and interactions on the official Sina Weibo account of a Chinese university from 2018 to 2023. This model simulates to infer the optimal decisions that trigger university social media engagement.
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Lee, Wen-Yu, Yin-Hsi Kuo, Winston H. Hsu, and Kiyoharu Aizawa. "City-view image location identification by multiple geo-social media and graph-based image cluster refinement." Journal of Visual Communication and Image Representation 41 (November 2016): 200–211. http://dx.doi.org/10.1016/j.jvcir.2016.09.017.
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Lukashenko, M. A., N. V. Gromova, and A. A. Ozhgikhina. "Digital Media Image of Business University Professor." Vysshee Obrazovanie v Rossii = Higher Education in Russia 30, no. 7 (September 8, 2021): 91–104. http://dx.doi.org/10.31992/0869-3617-2021-30-7-91-104.
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Digitalization of business and society inevitably affects almost all spheres, and education is not an exception. New high-tech tools and solutions are rapidly coming into this industry, without which further development and implementation of the educational process is no longer possible. Today target audience of any educational organizations is informationally advanced and prefers to source useful information from social networks, often making business decisions based on it. Such conditions put forward new requirements for educational organizations to increase their activity in social networks and, above all, to form a digital image. Professors are the face of any educational organization. Inasmuch as they are the subjects who directly interact with students, their personal digital image plays an important role in shaping corporate image of the university. Relevance of this article is in the research of the digital image process formation by professors of business universities, which are the flagships and market-oriented subjects of local higher education.The article aims to identify the current state of forming the digital image of teachers of entrepreneurial universities in social networks. To achieve the goal, the article discusses the features of an entrepreneurial university and the characteristics of its corporate image, shows the need to form a teacher’s digital image and identifies strategies for such formation in social networks. The study of the activity of Russian entrepreneurial universities’ teachers in social networks was carried out and the comparison of the results with the similar activity of foreign universities’ teachers was made.
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Kudeshia, Chetna, and Arun Mittal. "Social Media." International Journal of Online Marketing 5, no. 2 (April 2015): 37–57. http://dx.doi.org/10.4018/ijom.2015040103.
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From Obama's success to the Arab spring, from Kolaveri Di in India to Gangnam style, social media is omnipresent. We no longer go to the news, news finds us; we no longer visit merchandise, merchandise find us; social media has shrunk the globe beyond imagination. Social media is based on the combined notion of influence and participation -.tools that synchronize their voice with the company's voice and that combined voice affects the next customer. The development of social media networks have made it feasible for the customers to speak to thousands of other customers concerning a particular brand or a company. This communication between one to several additionally referred to as word-of-mouth marketing, isn't new to marketing, but the distinction is that currently these communications are on the far side boundaries. With the growing effect of social media on consumer buying behavior, it becomes imperative for a business to understand the competitive advantages of assorted social media avenues across diverse markets. As the world of online marketing is continuously progressing, the marketers must understand how these changes may influence buyer practices, and consequently promotional programs and strategies. Choices on how and when to successfully use the traditional as well as the social media alternatives require careful thought and consideration. This paper aims to throw light on the recent social media marketing strategies and demonstrates how this platform of online networking helps organizations to captivate their clients in a finer manner, thus building a stronger relationship with them. Also the present paper offers significant understanding to the marketers in knowing the vital role social media marketing plays in the formation of a strong brand. The present paper is conceptual in nature, and through the intensive literature review identifies the latest social media practices being adopted by the 21st century marketers. The study is an endeavor to see how advertisers are utilizing social networking as a strategic tool for advancement. The study finds that enhanced presence and communication on various social media channels help the firms in creating a better brand image while reducing promotional budgets. The paper additionally indicates how the exceptional attributes of correspondence by means of online networking help organizations not only in building a superior connection with their customers but also in converting them into their brand advocates. Thus, these network platforms are helping the businesses to engage with the purchasers, influencing them, connecting with them and finally changing them into their evangelists.
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Jain, Himani. "Images Spam Detection on Online Social Media using CNN with Pre-Trained Model." International Journal for Research in Applied Science and Engineering Technology 12, no. 6 (June 30, 2024): 2427–38. http://dx.doi.org/10.22214/ijraset.2024.63490.
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Abstract: Nowadays attackers move to image spam techniques instead of text based. The Majority of conventional techniques solely possess the capability to identify spam confined to textual content and hyperlinks. In this research we have done “Deep Convolutional Neural Networks” (DCNNs)in conjunction with pre-trained architectures. Image classification is one of the areas that has increased in the last decade very rapidly. But due to the less computational resources it become very challenging to train a good image classification model. With the help of Transfer learning, we can overcome this type of situation and can build a good image classification model. Our proposed model utilizes deep convolutional neural networks (DCNNs) along with pre-trained architectures. By fine-tuning this pre-trained model on the specific image dataset, the model can effectively learn to detect image- based spam content. Our suggested model surpasses contemporary state-of-the-art detection models concerning both accuracy and efficiency in the realm of the image spam identification.
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Liu, Yan, and Shuo Zhu. "Multimodal Wireless Situational Awareness-Based Tourism Service Scene." Journal of Sensors 2021 (December 22, 2021): 1–9. http://dx.doi.org/10.1155/2021/5503333.
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Community platforms featuring user sharing and self-expression in social media generate big data on tourism resources, which, if fully utilized in a smart tourism system driven by high-tech and new technologies, will bring new life to the field of smart tourism research and will play an important role in the development of Internet+ tourism. However, tourism data in social media has the following characteristics: diversity, redundancy, heterogeneity, and intelligence. To address the characteristics of tourism data in social media, this thesis focuses on the following challenges: it is difficult to efficiently obtain tourism visualization information (text and images) in social media; it is difficult to effectively utilize tourism multimodal heterogeneous information; it is difficult to properly retrieve multimedia entity information of tourism attractions; and it is difficult to reasonably construct tourism personalized recommendation models. In this paper, an image search reordering method based on a hybrid feature graph model is proposed to realize the rapid acquisition of high-quality Internet images from the web using hybrid visual features and graph models, thus providing data security for the analysis of social media-based tourism images. To address the shortcomings of current search engines for image retrieval, visual information is used to bridge the problem of semantic gap between text-based search and images. To address the limitation of single visual features, we use latent semantic analysis to fuse multiple visual features to obtain hybrid features, which not only combine multiple single features but also preserve the potential relationship between these features. To address the shortcomings of the reordering methods based on classification and clustering, a reordering framework based on the graph model is used to reorder the images and finally complete the image search reordering based on the hybrid feature graph model. This method can obtain image information in social media with high efficiency and quality and then prepare for the subsequent work of tourism image analysis mining and personalized recommendation.
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Wang, Jiakun. "The Impact of Social Media on Body Image Perception and Eating Disorders." Journal of Innovations in Medical Research 2, no. 9 (September 2023): 36–40. http://dx.doi.org/10.56397/jimr/2023.09.06.
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This essay discusses the negative impact of social media on body image and the promotion of healthier attitudes towards food and body diversity. It explores the sociocultural and psychological factors that contribute to susceptibility to social media influence, such as self-esteem, body image dissatisfaction, the need for social approval, perfectionism, and social comparison orientation. Peer pressure and social comparison are identified as significant influences on social media platforms. Potential solutions and interventions are proposed, including media literacy education, promoting body positivity and diversity, encouraging responsible social media use, developing evidence-based resources, fostering a supportive online community, collaborating with influencers and content creators, and encouraging individuals to seek professional help. By addressing these issues, we can work towards mitigating the negative impact of social media on body image and promoting healthier attitudes towards food and body diversity.
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P, Sathyaraj, Sudharshanam V, Navarajan J, and Vijayalakshmi P. "BUSINESS INTELLIGENCE BASED RECURRENT NEURAL NETWORK RNN TECHNIQUES FOR SOCIAL MEDIA IMAGE CONTENT CLASSIFICATION." ICTACT Journal on Image and Video Processing 14, no. 3 (February 1, 2024): 3209–15. http://dx.doi.org/10.21917/ijivp.2024.0457.
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Social media platforms like X and Facebook generate vast amounts of image content daily, necessitating automated methods for classification and analysis. Integrating Business Intelligence (BI) with Recurrent Neural Network (RNN) techniques presents a promising approach to extract valuable insights from this data. This study proposes a methodology for social media image content classification using a hybrid architecture combining Convolutional Neural Networks (CNNs) for feature extraction and RNNs for capturing temporal dependencies. The model is trained on labeled image datasets from X and Facebook, leveraging transfer learning and data augmentation techniques. The contribution lies in the fusion of BI and deep learning techniques, offering a scalable solution for real-time image content classification on social media platforms. This approach enables businesses to streamline marketing analysis, trend detection, and content moderation tasks efficiently. Experimental results demonstrate the effectiveness of the proposed methodology, achieving high accuracy in classifying diverse image content. The model''s performance is validated through comprehensive evaluation metrics, showcasing its robustness and applicability in real-world scenarios.
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Faisal, Aekram, and Iwan Ekawanto. "The role of Social Media Marketing in increasing Brand Awareness, Brand Image and Purchase Intention." Indonesian Management and Accounting Research 20, no. 2 (August 23, 2022): 185–208. http://dx.doi.org/10.25105/imar.v20i2.12554.
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In recent years, social media is not only used for social interaction activities, but is also used as a medium for doing business. Especially at this time when the whole world is facing the covid 19 pandemic, where most countries make decisions about closing and restricting several physical places, which have been used to carry out business activities, entrepreneurs are trying to optimize digital media and social media as a strategy to market their products. This study aims to determine the role of social media marketing in increasing brand awareness, brand image and purchase intention. The design of this research is hypothesis testing. The study uses the Structural Equation Modeling (SEM) method with a sample of 331 respondents who are active users of social media in Indonesia, for at least 2 years and have purchased products marketed on social media. The results show that social media marketing activities based on entertainment, interaction, trendiness, customization, and word-of-mouth have a positive influence on brand awareness, brand image, and purchase intention. Furthermore, brand awareness has a positive influence in mediating social media marketing activities on purchase intentions, and brand image also has a positive influence in mediating social media marketing activities on purchase intentions. Thus, so that consumer intentions to buy products can increase, online shop owners can increase awareness and positive image of the brand, and to increase brand awareness and positive image of the brand, online shop owners can increase their marketing activities through social media.Keywords: Social Media Marketing, Brand Awareness, Brand Image, Purchase Intention.
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Febrianur I. F. S. Putra, Suhita W. Setyahuni, Mahmud Mahmud, and Awanis L. Haziroh. "Workshop Peningkatan Organization Image SDN 2 Mojosari Kabupaten Rembang." ARDHI : Jurnal Pengabdian Dalam Negri 1, no. 6 (December 31, 2023): 71–77. http://dx.doi.org/10.61132/ardhi.v1i6.110.
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A good organization image is one of the factors for an organization to be able to achieve competitive advantage. To create a good image of an organization, an effective communication process is needed to the public. Online communication media and social media are effective organizational communication tools and can improve the organization's image. This community service activity is packaged in the form of training which aims to improve the skills of SDN 2 Mojosari teachers in mastering online media and social media as a means of organizational communication. Effective organizational communication can create a good image of the organization. This training activity has an impact on increasing the abilities of teachers and changing digital-based organizational communication strategies to improve the organization's image as one of the organization's competitive advantages.Organization image, Social Media, Organization Communication, Competitive Advantage
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Nagibina, Irina G., та Viktoriya G. Morgun. "Метафорический медиаобраз пожилого человека в китайской социальной сети «Доуинь»". Vestnik of Northern (Arctic) Federal University. Series Humanitarian and Social Sciences, № 3 (20 вересня 2024): 101–8. http://dx.doi.org/10.37482/2687-1505-v365.
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Currently, short-form video hosting services are gaining popularity in China, which means that their influence on society is rapidly increasing. Multimodal perceptual images constructed by these short videos have integrity, structure and constancy. One of the most well-known social media platforms in China for watching short videos and creating a certain image is Douyin. It is important to note that one of the key media images broadcast in this social network is the media image of an elderly person. This can be explained not only by the attractiveness of an elderly character and his/her hobbies, but also by the fact that the elderly population in China has been growing (rapid ageing phenomenon) due to an increase in life expectancy and declining birthrate. The article analyses the metaphorical model that actualizes various features of the representation of the media image of an elderly person in Chinese media discourse. The screening of Douyin videos conducted by the authors is based on such methods as contextual and descriptive analysis, as well as cultural interpretation. The paper turns to the theory of metaphorical modelling and views the concept of metaphor not only as a separate type of discourse, but also as a means of conceptualizing an image in the minds of native speakers. The most frequent metaphors used to create a media image of an elderly person are as follows: “an elderly person is a child”, “an elderly person is a saint/immortal being” and “an elderly person is a treasure/precious thing”. The study also points out that in the Chinese media space, the image of an elderly person is positive since an older adult has a number of skills and characteristics that meet the needs and interests of the majority of the platform’s users.
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Yan, Wei Qi, Xiaotian Wu, and Feng Liu. "Progressive Scrambling for Social Media." International Journal of Digital Crime and Forensics 10, no. 2 (April 2018): 56–73. http://dx.doi.org/10.4018/ijdcf.2018040104.
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Despite research work achieving progress in preserving the privacy of user profiles and visual surveillance, correcting problems in social media have not taken a great step. The reason is the lack of effective modelling, computational algorithms, and resultant evaluations in quantitative research. In this article, the authors take social media into consideration and link users together under the umbrella of social networks so as to exploit a way that the potential problems related to media privacy could be solved. The author's contributions are to propose tensor product-based progressive scrambling approaches for privacy preservation of social media and apply our approaches to the given social media which may encapsulate privacy before being viewed so as to achieve the goal of privacy preservation in anonymity, diverse and closeness. These approaches fully preserve the media information of the scrambled image and make sure it is able to be restored. The results show the proposed privacy persevering approaches are effective and have outstanding performance in media privacy preservation.