Relevant bibliographies by topics / Micro-messages

Academic literature on the topic 'Micro-messages'

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Published: 25 May 2024

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Journal articles on the topic "Micro-messages"

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Gupta, Mukul, Pradeep Kumar, and Bharat Bhasker. "Clustering of Micro-Messages Using Similarity Upper Approximation." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 25, no. 01 (February 2017): 53–79. http://dx.doi.org/10.1142/s0218488517500039.

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Microblogging platforms like Twitter, Tumblr and Plurk have radically changed our lives. The presence of millions of people has made these platforms a preferred channel for communication. A large amount of User Generated Content, on these platforms, has attracted researchers and practitioners to mine and extract information nuggets. For information extraction, clustering is an important and widely used mining operation. This paper addresses the issue of clustering of micro-messages and corresponding users based on the text content of micro-messages that reflect their primitive interest. In this paper, we performed modification of the Similarity Upper Approximation based clustering algorithm for clustering of micro-messages. We compared the performance of the modified Similarity Upper Approximation based clustering algorithm with state-of-the-art clustering algorithms such as Partition Around Medoids, Hierarchical Agglomerative Clustering, Affinity Propagation Clustering and DBSCAN. Experiments were performed on micro-messages collected from Twitter. Experimental results show the effectiveness of the proposed algorithm.
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Dunkel, Anke, Kent Nakamoto, and Peter J. Schulz. "Micro-cultural customization of organ donation propagation messages." Patient Education and Counseling 101, no. 5 (May 2018): 824–29. http://dx.doi.org/10.1016/j.pec.2017.12.019.

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Shen, Zheng. "A persuasive eWOM model for increasing consumer engagement on social media: evidence from Irish fashion micro-influencers." Journal of Research in Interactive Marketing 15, no. 2 (May 31, 2021): 181–99. http://dx.doi.org/10.1108/jrim-10-2019-0161.

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Purpose This study aims to find how can fashion micro-influencers and their electronic word-of-mouth (eWOM) messages increase consumer engagement on social media, focusing on micro-influencers’ influence, typology, eWOM content and consumer engagement. Design/methodology/approach A total of 20,000 microblogs were collected from Irish fashion micro-influencers and analyzed through keyword classification and content analysis in NVivo. The determinants of eWOM persuasiveness for consumer engagement on social media were investigated based on Sussman and Siegal’s information adoption model. Findings The study finds that among the four types of micro-influencers, market mavens and their eWOM messages have the highest impact on consumer engagement on social media, and it presents a repetitive and persuasive eWOM model of market mavens to increase consumer participation. Also, the study discovers that micro-influencers’ occasion-related microblogs have an increasing impact on consumer interactions whereas microblogs with brands have a decreasing engagement with consumers on social media. Originality/value This study advances prior studies on the relationship between influencers’ eWOM messages and consumer participation on social media by the development of a persuasive eWOM model of micro-influencers to increase consumer engagement and fill in the lack of relevant literature. Also, findings provide actionable insights for marketing communication practitioners to persuade consumers to participate in eWOM communications and establish strong consumer-brand relationships on social media.
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Kipp, Peter C., Yibo (James) Zhang, and Amanuel F. Tadesse. "Can Social Media Interaction and Message Features Influence Nonprofessional Investors' Perceptions of Firms?" Journal of Information Systems 33, no. 2 (February 1, 2018): 77–98. http://dx.doi.org/10.2308/isys-52067.

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ABSTRACT We investigate the impact of social media messages on nonprofessional investors' assessments of management credibility and firm value. In a between-participants experiment, we examine the joint effect of social media message vividness, valence, and micro-blogger influence on nonprofessional investors' assessments of management credibility and firm value. We find that when social media messages are pallid and negative (positive), high micro-blogger influence decreases (increases) nonprofessional investors' assessments of management credibility. In contrast, the effect is absent when messages are vivid. Further, we find that the effect of micro-blogger influence on nonprofessional investors' assessments of blogger credibility and management credibility is mediated by social media interactions. The assessment of management credibility, in turn, significantly impacts nonprofessional investors' firm valuation assessment. The results have implications for regulators (SEC 2013) that may wish to update their guidance to managers on how to monitor or even control nonprofessional investors' interaction on social media platforms. Data Availability: Contact the authors.
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Ali, Mubashir, Anees Baqir, Giuseppe Psaila, and Sayyam Malik. "Towards the Discovery of Influencers to Follow in Micro-Blogs (Twitter) by Detecting Topics in Posted Messages (Tweets)." Applied Sciences 10, no. 16 (August 18, 2020): 5715. http://dx.doi.org/10.3390/app10165715.

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Micro-blogs, such as Twitter, have become important tools to share opinions and information among users. Messages concerning any topic are daily posted. A message posted by a given user reaches all the users that decided to follow her/him. Some users post many messages, because they aim at being recognized as influencers, typically on specific topics. How a user can discover influencers concerned with her/his interest? Micro-blog apps and web sites lack a functionality to recommend users with influencers, on the basis of the content of posted messages. In this paper, we envision such a scenario and we identify the problem that constitutes the basic brick for developing a recommender of (possibly influencer) users: training a classification model by exploiting messages labeled with topical classes, so as this model can be used to classify unlabeled messages, to let the hidden topic they talk about emerge. Specifically, the paper reports the investigation activity we performed to demonstrate the suitability of our idea. To perform the investigation, we developed an investigation framework that exploits various patterns for extracting features from within messages (labeled with topical classes) in conjunction with the mostly-used classifiers for text classification problems. By means of the investigation framework, we were able to perform a large pool of experiments, that allowed us to evaluate all the combinations of feature patterns with classifiers. By means of a cost-benefit function called “Suitability”, that combines accuracy with execution time, we were able to demonstrate that a technique for discovering topics from within messages suitable for the application context is available.
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Liu, Pei Yu, Yan Hui Zhang, Jing Xun Wei, and Xiu Yan Hou. "MicroBlog Orientation Analysis Based on Sentiment Symbol." Applied Mechanics and Materials 687-691 (November 2014): 1933–37. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1933.

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As a new social networking media, Micro-blog is recognized by more and more people gradually, the orientation analysis of Micro-blog short text messages has become a hotspot in the field of data mining. At present, the research of Micro-blog orientation analysis mainly concentrate in the text, without considering the impact of other emotional factors. By analyzing and studying Sina Micro-blog, this paper added new words and emoticons in the basis of traditional emotional dictionary to construct special Micro-blog dictionary. Meanwhile, it analyzed rhetoric and sentence to improve the effect of orientation analysis. The experimental results showed that the method in Micro-blog orientation analysis obtained better performance.
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Al-Zubi, Ahmad Ali. "A New Method for Extracting Key Terms from Micro-Blogs Messages Using Wikipedia." Research Journal of Applied Sciences, Engineering and Technology 6, no. 21 (November 20, 2013): 4070–76. http://dx.doi.org/10.19026/rjaset.6.3512.

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Pavithra, R., and A. R. Mohamed Shanavas. "Sentiment Analysis about Smart Phones Using Twitter Corpus by Deep Learning Approach." Asian Journal of Computer Science and Technology 8, S2 (March 5, 2019): 39–45. http://dx.doi.org/10.51983/ajcst-2019.8.s2.2027.

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Micro blogging websites are nothing but social media website to which user makes quick and frequent posts. Twitter is one of the well-known micro blog sites which offer the space for person which can read and put up messages that are 148 characters in duration. Twitter messages also are referred to as Tweets. And will use these tweets as raw facts. Then use a way that automatically extracts tweets into advantageous, bad or neutral sentiments. By the usage of the sentiment evaluation the consumer can recognize the feedback about the product or services before make a purchase. The organization can use sentiment evaluation to know the opinion of clients about their products, so can examine customer pleasure and in line with that they could improve their product. Now-a-days social networking sites are at the growth, so massive amount of data is generated. Millions of human beings are sharing their views each day on micro blogging sites, since it includes short and simple expressions. In this thesis, able to discuss approximately a paradigm to extract the sentiment from a famous micro running a blog carrier, Twitter, wherein customers submit their opinions for the whole thing. And can use the deep mastering algorithm to categories the twitters which incorporates Convolutional Neural Networks. The experimental end result is presented to demonstrate the use and effectiveness of the proposed system.
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Jiang, W., Y. Wang, M. H. Tsou, and X. Fu. "Using geo-targeted social media data to detect outdoor air pollution." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 553–54. http://dx.doi.org/10.5194/isprs-archives-xli-b2-553-2016.

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Outdoor air pollution has become a more and more serious issue over recent years (He, 2014). Urban air quality is measured at air monitoring stations. Building air monitoring stations requires land, incurs costs and entails skilled technicians to maintain a station. Many countries do not have any monitoring stations and even lack any means to monitor air quality. Recent years, the social media could be used to monitor air quality dynamically (Wang, 2015; Mei, 2014). However, no studies have investigated the inter-correlations between real-space and cyberspace by examining variation in micro-blogging behaviors relative to changes in daily air quality. Thus, existing methods of monitoring AQI using micro-blogging data shows a high degree of error between real AQI and air quality as inferred from social media messages. <br><br> In this paper, we introduce a new geo-targeted social media analytic method to (1) investigate the dynamic relationship between air pollution-related posts on Sina Weibo and daily AQI values; (2) apply Gradient Tree Boosting, a machine learning method, to monitor the dynamics of AQI using filtered social media messages. Our results expose the spatiotemporal relationships between social media messages and real-world environmental changes as well suggesting new ways to monitor air pollution using social media.
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Wang, Yan Ping. "Research on the Design and Application of Micro Blog Network Marketing into the Global Trade." Applied Mechanics and Materials 687-691 (November 2014): 4902–5. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.4902.

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The emergence and rapid development of Micro Blog has provided a new, swift and effective tool for the international trade. Nowadays this new tool is called Micro Blog internet marketing. Compared with blog, the micro log is much more convenient and the issued content is much more brief which makes the users issue messages timely and usually it is a much more effective channel for the readers and the bloggers to communicate with each other. Micro blog has quickly become a popular tool to communicate and every website has begun to open their own micro blog to propaganda their companies. The micro blog internet marketing can reduce the cost of international trade, improve trade efficiency and customer satisfaction and improve the enterprises’ awareness of competition. Therefore to lay much more emphasis on the role that the micro blog internet marketing has played in international trade is a must in the new century. This is also a way to increase the construction of internet information, thus regulating the micro internet marketing and promoting the healthy development of this field.
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Dissertations / Theses on the topic "Micro-messages"

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Cavalcante, Thiago 1989. "Authorship attribution on micro-messages = Atribuição de autoria em micro-mensagens." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/275539.

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Orientadores: Ariadne Maria Brito Rizzoni Carvalho, Anderson de Rezende Rocha
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica
Made available in DSpace on 2018-08-26T21:23:31Z (GMT). No. of bitstreams: 1 Cavalcante_Thiago_M.pdf: 3493838 bytes, checksum: 369bd6608e7326d0a998b426a1c7455b (MD5) Previous issue date: 2014
Resumo: Com o crescimento continuo do uso de midias sociais, a atribuição de autoria tem um papel imortante na prevenção dos crimes cibernéticos e na análise de rastros online deixados por assediadores, \textit{bullies}, ladrões de identidade entre outros. Nesta dissertação, nós propusemos um método para atribuição de autoria que é de cem a mil vezes mais rápido que o estado da arte. Nós também obtivemos uma acurácia 65\% na classificação de 50 autores. O método proposto se baseia numa representação de caracteristicas escalável utilizando os padrões das mensagens dos micro-blogs, e também nos utilizamos de um classificador de padrões customizado para lidar com grandes quantidades de dados e alta dimensionalidade. Por fim, nós discutimos a redução do espaço de busca na análise de centenas de suspeitos online e milões de micro mensagens online, o que torna essa abordagem valiosa para forense digital e aplicação das leis
Abstract: With the ever-growing use of social media, authorship attribution plays an important role in avoiding cybercrime, and helping the analysis of online trails left behind by cyber pranks, stalkers, bullies, identity thieves and alike. In this dissertation, we propose a method for authorship attribution in micro blogs with efficiency one hundred to a thousand times faster than state-of-the-art counterparts. We also achieved a accuracy of 65% when classifying texts from 50 authors. The method relies on a powerful and scalable feature representation approach taking advantage of user patterns on micro-blog messages, and also on a custom-tailored pattern classifier adapted to deal with big data and high-dimensional data. Finally, we discuss search space reduction when analysing hundreds of online suspects and millions of online micro messages, which makes this approach invaluable for digital forensics and law enforcement
Mestrado
Ciência da Computação
Mestre em Ciência da Computação
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Huet, Sylvie. "Modèles individu-centrés de systèmes sociaux : micro-modèles hybrides inspirés des données simulant le développement rural ; dynamiques collectives de filtrage et / ou de rejet des messages." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2013. http://tel.archives-ouvertes.fr/tel-00856248.

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Cette thèse a pour objet la modélisation individu-centrée des systèmes sociaux. Une première partie orientée aide à la décision présente un modèle d'évolution des populations rurales fortement inspiré des données. Une seconde partie, plus théorique, étudie divers mécanismes permettant à un individu d'accepter ou de résister à une influence sociale. Nous proposons tout d'abord un modèle individu-centré de la dynamique des municipalités rurales européennes, implémenté pour le département du Cantal. Nous proposons un nouvel algorithme de génération des populations initiales ne nécessitant pas d'échantillon de population (approche classique). Nous concevons et paramétrons un modèle de la dynamique de l'individu face au marché du travail basé sur les données de la " European Labour Force Survey ". Il inclut des heuristiques originales de transition d'états tel qu'actifs, inactifs, chômeurs, ... prenant en compte l'âge, la profession et le secteur d'activité de l'individu. Nous déterminons les dynamiques non fondés sur des données individuelles en testant la capacité de dynamiques simples à produire des résultats proches des données agrégées disponibles. Est ainsi conçu un modèle de mobilité résidentielle, expliquant partiellement la migration et intégrant décision de déménager et choix d'une nouvelle résidence. La seconde partie de la thèse étudie les effets collectifs de différents mécanismes permettant aux individus de résister à ou d'accepter une influence sociale. Un premier mécanisme étudié est un filtre cognitif impliquant qu'un individu ne reçoit pas une information incongruente ou peu importante. Les individus " filtreurs " exhibent le biais de primauté car leur attitude n'est déterminée que par les premiers éléments reçus et se montrent négatifs alors que le message diffusé par un media est neutre. Le taux d'individus négatifs dans la population est accru ou diminuer par l'échange direct d'information entre les individus. Un second mécanisme est un rejet de la tentative d'influence qui mène l'individu à différencier davantage son attitude de celle de son interlocuteur. Il intervient lorsque l'individu éprouve un inconfort lié au fait qu'il est à la fois en accord et en désaccord avec son interlocuteur. Le couplage de ce rejet à un mécanisme d'attraction entre individus en accord entraîne un nombre moindre de groupes d'opinion différentes à l'échelle de la population (ie par rapport au nombre de groupes obtenus avec le seul mécanisme d'attraction).
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Books on the topic "Micro-messages"

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Inc, Micro Focus, ed. Micro Focus COBOL/2: Error messages. Palo Alto, CA: Micro Focus Inc., 1988.

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Bundschuh, Rick, and Tom Finley. Micro Messages. Regal Books, 1995.

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Error messages manual for use with Micro Focus COBOL. 2nd ed. Newbury: Micro Focus, 1989.

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Bogdanović, Jelena. Nested in Its Own Shape. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190465186.003.0006.

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The concepts of total design of the Byzantine church based on the micro-architecture of canopies allow the expansion of their scale to include a macro-scale relative to the space in which they are found and which they denote. Two ultimate architectural models for the embodiment of the heavenly and earthly Jerusalem in a Byzantine-rite church are the Temple and the Holy Sepulchre. By focusing on Hagia Sophia, these two concepts and related architectural models are especially highlighted: first, the Biblical architectural models carried on the level of ideas—the Ark, the Tabernacle, the Temple, Heavenly Jerusalem—and second, the Tomb of Christ in Jerusalem as the seminal Christian site that palpably carried the pervasive salvific messages from the Holy Land to the Byzantine believers.
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Book chapters on the topic "Micro-messages"

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Sousa Silva, Rui, Gustavo Laboreiro, Luís Sarmento, Tim Grant, Eugénio Oliveira, and Belinda Maia. "‘twazn me!!! ;(’ Automatic Authorship Analysis of Micro-Blogging Messages." In Natural Language Processing and Information Systems, 161–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22327-3_16.

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Li, Yang, Yiheng Chen, Ting Liu, and Wenchao Deng. "Predicting the Popularity of Messages on Micro-blog Services." In Communications in Computer and Information Science, 44–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45558-6_4.

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Aykent, Sarp, and Cheryl Seals. "Exploring the Anonymity of Social Media Users Using Micro-messages." In Social Computing and Social Media, 14–24. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35915-6_2.

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Chen, Gaowei, and Ming M. Chiu. "Discussion Processes in Online Forums." In Advances in Computer and Electrical Engineering, 1702–13. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7598-6.ch125.

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Online discussion's information transparency, communication flexibility, and opportunities for reflection can enhance information processing, higher order thinking, and learning. Many group processes influence online discussants' creation of correct, new ideas (micro-creativity) and use of social cues. New ideas, justifications, disagreements, and questions in recent messages facilitate micro-creativity. Moreover, new ideas and justifications tend to reduce both positive and negative social cues during online discussions. While agreements elicit positive social cues, disagreements invite negative ones. Meanwhile, participants with more past posts than others often show more micro-creativity. Together, these mechanisms show how sequences of online messages create a local context that influences participants' correct outcomes and social relationships. By understanding these discussion processes, designers can improve online forum interfaces, and educators can help students participate, cooperate, and learn in online forums more effectively.
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Chen, Gaowei, and Ming M. Chiu. "Discussion Processes in Online Forums." In Encyclopedia of Information Science and Technology, Fourth Edition, 7969–79. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2255-3.ch693.

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Online discussions' information transparency, communication flexibility and opportunities for reflection, can enhance information processing, higher order thinking and learning. Many group processes influence online discussants' creation of correct, new ideas (micro-creativity) and use of social cues. New ideas, justifications, disagreements and questions in recent messages facilitate micro-creativity. Moreover, new ideas and justifications tend to reduce both positive and negative social cues during online discussions. While agreements elicit positive social cues, disagreements invite negative ones. Meanwhile, participants with more past posts than others often show more micro-creativity. Together, these mechanisms show how sequences of online messages create a local context that influences participants' correct outcomes and social relationships. By understanding these discussion processes, designers can improve online forum interfaces, and educators can help students participate, cooperate and learn in online forums more effectively.
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Webb, Lynne M., and Yuanxin Wang. "Techniques for Sampling Online Text-Based Data Sets." In Big Data, 655–75. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9840-6.ch030.

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The chapter reviews traditional sampling techniques and suggests adaptations relevant to big data studies of text downloaded from online media such as email messages, online gaming, blogs, micro-blogs (e.g., Twitter), and social networking websites (e.g., Facebook). The authors review methods of probability, purposeful, and adaptive sampling of online data. They illustrate the use of these sampling techniques via published studies that report analysis of online text.
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Guevara, Katherine. "Designing Text Message Learning to More Equitably Reach Students Wherever They Go." In TESOL Guide for Critical Praxis in Teaching, Inquiry, and Advocacy, 326–43. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-8093-6.ch016.

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This chapter describes how TESOL educators can partner with global aid organizations, local communities, and learners themselves to leverage low-tech yet innovative learning solutions like text-message lessons with the goal of more equitably reaching learners, particularly those affected by disruption to their education such as those who are migrants/refugees. Taking such action as advocates committed to closing opportunity gaps arising from social issues affecting language learning not only involves the TESOL educator in the six principles for exemplary teaching of English learners but also UN Sustainable Development Goals as a framework, trauma-informed teaching and learning, and the concept of text messages used as micro-learning. Through a UNICEF case study of practice in action, the author provides a stepwise how-to for redesigning curriculum into micro-learning appropriate for text-message delivery and offers considerations and recommendations for its dissemination, evaluation, and potential application to many other contexts and learner populations at scale.
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Hughes, Emily. "Introduction." In Studying Talk to Her, 9–10. Liverpool University Press, 2015. http://dx.doi.org/10.3828/liverpool/9781906733438.003.0002.

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This introductory chapter provides an overview of Pedro Almodóvar's Talk to Her (2002). The film offers much, both in terms of thematic analysis and micro analysis of the sound, performance, cinematography, editing, and mise-en-scène. Almodóvar can be considered to be a director who is a specialist in gender and the issue of gender identity is explored in Talk to Her, particularly the notion that gender characteristics are fluid and not fixed. Almodóvar's characters simultaneously embody and reject gender stereotypes and share both feminine and masculine attributes. Most of all, what makes Talk to Her such an interesting film to dissect, is the uneasy position that Almodóvar places the spectator in and how its messages and values create moral ambiguity. The film delivers morally complex, hazy messages about rape, voyeurism, and obsession and consequently, the spectator finds humour where they should find revulsion and sympathy where they should find anger. As a result, the film has sparked a great deal of critical, theoretical, and philosophical analysis, particularly around the issue of rape.
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Victor Rajan, K. "Sentiment Analysis of Social Media Using Artificial Intelligence." In Artificial Intelligence. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.113092.

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Social media refers to the development and sharing of sentiment, information, and interests, as well as other forms of opinion via virtual communities and networks. Nowadays, social networking and micro blogging websites are considered reliable sources of information since users may openly express their opinions in these forums. An investigation of the sentiment on social media could assist decision-makers in learning how consumers feel about their services, products, or policies. Extracting emotion from social media messages is a difficult task due to the difficulty of Natural Language Processing (NLP). These messages frequently use a combination of graphics, emoticons, text, etc. to convey the sentiment or opinion of the general people. These claims, known as eWOM (Electronic Word of Mouth), are quite common in public forums where people may express their opinions. A classification issue arises when categorizing the sentiment of eWOM as positive, negative, or neutral. We could not use standard NLP tools to examine social media sentiment. In this chapter, we will study the role of Artificial Intelligence in identifying the sentiment polarity of social media. We will apply ML(Machine Learning) methods to resolve this classification issue without diving into the difficulty of eWOM parsing.
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Stein, Michael D., and Sandro Galea. "In Social Media We Trust." In Pained, 187–90. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780197510384.003.0054.

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This chapter discusses the possible impact of micro-targeting in social media for health. For example, a hypothetical social media platform called InstaTwitBook had an algorithm that could accurately judge that a user was suicidal from changes in the language she communicated online. Then that site’s administrators could send this at-risk person a gentle message suggesting that she is showing warning signs of depression, or maybe even nudge her toward help by sending advertisements about local mental health counseling. What if 3,500 persons could be reliably identified and sent such messages this year, and that one in 100 messages would lead to care-seeking, averting 35 suicides? Would this not be worthwhile? And it is not just InstaTwitBook that has the power of detection. Phone companies may be able to tell from someone’s voice if he or she is depressed and use that information to identify who may benefit from mental health help. However, there are challenges that arise from this approach—challenges like inevitable inaccuracy, false-positive results, and the sending of notifications to persons who are not suicidal. As such, more research on this approach is needed, which would require social media companies to be more open to third-party investigators using their data.
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Conference papers on the topic "Micro-messages"

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Brocardo, Marcelo Luiz, and Issa Traore. "Continuous authentication using micro-messages." In 2014 Twelfth Annual Conference on Privacy, Security and Trust (PST). IEEE, 2014. http://dx.doi.org/10.1109/pst.2014.6890938.

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Tsur, Oren, Adi Littman, and Ari Rappoport. "Scalable multi stage clustering of tagged micro-messages." In the 21st international conference companion. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2187980.2188157.

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Costa, Joana, Catarina Silva, Mario Antunes, and Bernardete Ribeiro. "The impact of longstanding messages in micro-blogging classification." In 2015 International Joint Conference on Neural Networks (IJCNN). IEEE, 2015. http://dx.doi.org/10.1109/ijcnn.2015.7280731.

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Laboreiro, Gustavo, Luís Sarmento, Jorge Teixeira, and Eugénio Oliveira. "Tokenizing micro-blogging messages using a text classification approach." In the fourth workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1871840.1871853.

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Aykent, Sarp, and Gerry Dozier. "AARef: Exploiting Authorship Identifiers of Micro-Messages with Refinement Blocks." In 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 2020. http://dx.doi.org/10.1109/icmla51294.2020.00169.

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Aykent, Sarp, and Gerry Dozier. "Author Identification of Micro-Messages via Multi-Channel Convolutional Neural Networks." In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2020. http://dx.doi.org/10.1109/smc42975.2020.9283214.

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Ahmed, Syed, KV Charan, V. Sudha, H. Suma, M. Sindhu, J. Ranjani, and Prerana Jayaprakash. "Enhancing Accessibility of Messages Using Clustering and Labeling In Micro blogging’s." In Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India. EAI, 2021. http://dx.doi.org/10.4108/eai.16-5-2020.2304025.

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Munusamy, Shankar, Michael Nelson, and Ronald Torry. "Micro-dosing Mindfulness and Wellness Messages into Pharmacology Classrooms Improves Pharmacy Students’ Resilience." In ASPET 2024 Annual Meeting Abstract. American Society for Pharmacology and Experimental Therapeutics, 2024. http://dx.doi.org/10.1124/jpet.019.872160.

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Theophilo, Antonio, Luis A. M. Pereira, and Anderson Rocha. "A Needle in a Haystack? Harnessing Onomatopoeia and User-specific Stylometrics for Authorship Attribution of Micro-messages." In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. http://dx.doi.org/10.1109/icassp.2019.8683747.

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Martino, Giovanni Da San, Stefano Cresci, Alberto Barrón-Cedeño, Seunghak Yu, Roberto Di Pietro, and Preslav Nakov. "A Survey on Computational Propaganda Detection." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/672.

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Abstract:
Propaganda campaigns aim at influencing people's mindset with the purpose of advancing a specific agenda. They exploit the anonymity of the Internet, the micro-profiling ability of social networks, and the ease of automatically creating and managing coordinated networks of accounts, to reach millions of social network users with persuasive messages, specifically targeted to topics each individual user is sensitive to, and ultimately influencing the outcome on a targeted issue. In this survey, we review the state of the art on computational propaganda detection from the perspective of Natural Language Processing and Network Analysis, arguing about the need for combined efforts between these communities. We further discuss current challenges and future research directions.
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