Relevant bibliographies by topics / Twitter behaviour

Academic literature on the topic 'Twitter behaviour'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Twitter behaviour"

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ALGARNI, ABDULLAH AHMED. "THE ROLE OF SOCIAL NETWORKS IN PROMOTING POSITIVE BEHAVIOUR DURING COVID-19 CRISIS AMONGST A SAMPLE OF USERS IN SAUDI SOCIETY: TWITTER AS A MODEL." AD ALTA: 12/01 12, no. 1 (June 30, 2022): 7–16. http://dx.doi.org/10.33543/1201716.

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This study seeks analysing Twitter social network role in promoting positive behaviour during COVID-19 crisis and exploring the relationship between them. It targets identifying Twitter positive behaviour level differences through variables of gender, age, marital status, residence status, administrative region, and Twitter using size. An online questionnaire was used on a validity-and-stability verified sample of (586) individual Twitter users in the Kingdom of Saudi Arabia. Sample members approved Twitter users’ positive behaviour during COVID-19 crisis. They agreed that the positive behaviour level was medium with a Twitter effect of (19.4%). There were both a positive, medium-strong correlation between Twitter daily use and a statistically significant correlation between one - session Twitter using and positive behaviour promotion. However, there were statistically significant differences in positive behaviour promotion when using Twitter between social status favouring singles, residence status favouring residents, age favouring those under 21, administrative region favouring the southern region, usage period favouring network daily and two days - users, and browsing time favouring much Twitter users .The study recommends conducting studies on positive social behaviour and its dimensions to broadly generalise results. Studies on the Internet of behaviour and artificial intelligence are needed to analyse the positive behaviour expected by social networks users to enhance opportunities. It also stressed children and adolescents’ digital social education to prepare community members for effective online participation, the activation of public and private services-providing agencies Twitter accounts, interacting positively with users' questions and responses, and substituting fixed stereotypes by interesting interactive patterns.
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Klotz, Christine, Coskun Akinalp, and Herwig Unger. "Clustering user behaviour patterns on Twitter." International Journal of Social Network Mining 2, no. 3 (2016): 203. http://dx.doi.org/10.1504/ijsnm.2016.082632.

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Akinalp, Coskun, Christine Klotz, and Herwig Unger. "Clustering user behaviour patterns on Twitter." International Journal of Social Network Mining 2, no. 3 (2016): 203. http://dx.doi.org/10.1504/ijsnm.2016.10003518.

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Gabriel, T. Nyitse, Terhile Agaku, and Cordelia Clayton. "Influence of Social Media on Abuja Youths Behaviour in 2019 General Elections: A Study of Twitter." RESEARCH JOURNAL OF MASS COMMUNICATION AND INFORMATION TECHNOLOGY 8, no. 1 (October 6, 2022): 63–74. http://dx.doi.org/10.56201/rjmcit.v8.no1.2022.pg63.74.

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This study ‘‘Influence of Social Media on Abuja Youths Voting Behaviour in 2019 General Elections: a study of Twitter’’ was conducted to ascertain how Twitter can be engaged as a platform for influencing voting behaviour particularly on youths in the city of Abuja. Anchored on Technology Determinism theory. the survey research design was adopted with online questionnaire as instrument for data collection, on a sample size of 100 respondents. Findings from the study revealed that ‘Twitter’ as a social media platform play a vital role in influencing youths, the study also found out that ‘Twitter’, was effective in enhancing voters behavior. Based on the findings the study concludes that Twitter which is one of the most common social media platform especially among youths, play crucial role in influencing voters behavior to some extent, despite the challenge of it being banned by the Federal Government lately. Thus the study recommends that more political parties should be encouraged to have a noticeable presence on the internet. Also the Federal Government should intensify its ICT drive in education and other sectors of the country as the reach of the social media surpasses that of any traditional media
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Azwar, Azmiera Izzati, and Suet Nie Kho. "Factors Influencing Young Malaysians’ Political Information Seeking Behaviour on Twitter." Jurnal Komunikasi: Malaysian Journal of Communication 38, no. 3 (September 30, 2022): 87–105. http://dx.doi.org/10.17576/jkmjc-2022-3803-06.

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Youth participation in political discourses is an important element that needs to be looked into urgently in Malaysia. This is especially so with the historical milestone of the Undi18 constitutional amendment allowing youth from 18 years old to vote in the 15th General Election. This research was initiated to investigate the youth's behaviour in terms of attitude, awareness, and involvement in politics via social media, specifically Twitter. In this study, involvement in politics is described as youths' political information seeking behaviour on Twitter in relation to political attitudes such as political self-efficacy, situational political involvement, government trust, and processing of information, that is perceived information quality. An online survey form was disseminated across Twitter using snowball sampling for Klang Valley Twitter users aged between 18 to 30. The results garnered from 314 respondents revealed significant relationships between independent variables (self-efficacy, situational, political involvement, government trust, and information quality) and the dependent variable (Twitter motivation). It was hoped that this study would help researchers better grasp the pattern on how Malaysian youth use Twitter to get political information. This study may also provide important information on the online diffusion and consumption of political information through social media like Twitter. Keywords: Political information-seeking behaviour, processing information, youth, Twitter, Malaysia.
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Rachmawati, Iva, Machya Astuti Dewi, Frans Richard Kodong, and Panji Dwi Ashrianto. "Trump and Biden's Covid 19 Policy Narrative on Twitter." RSF Conference Series: Business, Management and Social Sciences 1, no. 4 (October 22, 2021): 1–17. http://dx.doi.org/10.31098/bmss.v1i4.280.

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Social media can be one of the tools of state diplomacy to provide information to the public, change public perceptions and ultimately influence public behaviour. During the pandemic, social media has become one of the strategic diplomatic tools to reach the public and governments of other countries. In addition to conveying information about state policies in dealing with the pandemic, social media is also a means for the state to influence the public and other countries in taking a stand against the pandemic. This article looks at the policies and communication efforts of the two American Presidents on Twitter social media related to the Covid19 Pandemic through the descriptive analysis method. A structural approach to the concept of social media diplomacy is used to show that the narrative on Twitter influences the perception and behaviour of its users. This research found that the different narratives on Twitter and the differences in user perceptions and behaviours, indicating that social media diplomacy has a real impact on user perceptions and behaviour.
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Hodeghatta, Umesh Rao, and Sangeeta Sahney. "Understanding Twitter as an e-WOM." Journal of Systems and Information Technology 18, no. 1 (March 14, 2016): 89–115. http://dx.doi.org/10.1108/jsit-12-2014-0074.

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Purpose – This paper aims to research as to how Twitter is influential as an electronic word-of-mouth (e-WOM) communication tool and thereby affecting movie market. In present days, social media is playing an important role in connecting people around the globe. The technology has provided a platform in the social media space for people to share their experiences through text, photos and videos. Twitter is one such online social networking media that enables its users to send and read text-based messages of up to 140 characters, known as “tweets”. Twitter has nearly 200 million users and billions of such tweets are generated by users every other day. Social media micro-blogging broadcasting networks such as Twitter are transforming the way e-WOM is disseminated and consumed in the digital world. Twitter social behaviour for the Hollywood movies has been assessed across seven countries to validate the two basic blocks of the honeycomb model – sharing and conversation. Twitter behaviour was studied for 27 movies in 22 different cities of seven countries and for six genres with a total tweets of 9.28 million. The difference of Twitter social media behaviour was compared across countries, and “sharing” and “conversation” as two building blocks of the honeycomb model were studied. t-Test results revealed that the behaviour is different across countries and across genres. Design/methodology/approach – The objective of the paper is to analyse Twitter messages on an entertainment product (movies) across different regions of the world. Hollywood movies are released across different parts of the world, and Twitter users are also in different parts of the world. The objective is to hence validate “conversation” and “sharing” building blocks of the honeycomb model. The research is confined to analysing Twitter data related to a few Hollywood movies. The tweets were collected across nine different cities spanning four different countries where English language is prominent. To understand the Twitter social media behaviour, a crawler application using Python and Java was developed to collect tweets of Hollywood movies from the Twitter database. The application has incorporated Twitter application programming interfaces (APIs) to access the Twitter database to extract tweets according to movies search queries across different parts of the world. The searching, collecting and analysing of the tweets is a rather challenging task because of various reasons. The tweets are stored in a Twitter corpus and can be accessed by the public using APIs. To understand whether tweets vary from one country to another, the analysis of variance test was conducted. To assess whether Twitter behaviour is different, and to compare the behaviour across countries, t-tests were conducted taking two countries at a time. The comparisons were made across all the six genres. In this way, an attempt was made to obtain a microscopic view of the Twitter behaviour for each of the seven countries and the six genres. Findings – The findings show that the people use social media across the world. Nearly 9.28 million tweets were from seven countries, namely, USA, UK, Canada, South Africa, Australia, India and New Zealand for 27 Hollywood movies. This is indicative of the fact that today, people are exchanging information across different countries, that people are conversing about a product on social media and people are sharing information about a product on social media and, thus, proving the hypothesis. Further, the results indicate that the users in USA, Canada and UK, tweet more than the other countries, USA and UK being the highest in tweets followed by the Canada. On the other hand, the number of tweets in Australia, India and South Africa are low with New Zealand being the lowest of all the countries. This indicates that different countries’ users have different social media behaviour. Some countries use social media to communicate about their experience more than in some other country. However, consumers from all over the world are using Twitter to express their views openly and freely. Originality/value – This research is useful to scholars and enterprises to understand opinions on Twitter social media and predict their impact. The study can be extended to any products which can lead to better customer relationship management. Companies can use the Internet and social media to promote and get feedback on their products and services across different parts of the world. Governments can inform the public about their new policies, benefits of governmental programmes to people and ways to improve the Internet reach to more people and also for creating awareness about health, hygiene, natural calamities and safety.
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DÜNDAR, Mahire Armağan, and Fırat TUFAN. "Sosyal Ağ Sitelerinde Sosyal Karşılaştırma Davranışı: Instagram- Twitter Karşılaştırması." Yeni Medya Dergisi 2022, no. 12 (June 30, 2022): 1–16. http://dx.doi.org/10.55609/yenimedya.1051044.

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The purpose of this study is to examine social comparison behavior on social networking sites (SNS). Quantitative research method based on the closed-ended questionnaire technique was used in the study in which social comparison behavior was examined on image-based SNS, Instagram and text-based SNS, Twitter. Findings show that; individuals make social comparisons more in physical environments than on SNS. The level of social comparison is higher on Instagram compared to Twitter. Individuals are more frequently engaged in upward comparisons than downward comparisons on both Instagram and Twitter. Wealth is the domain in which individuals make comparisons the most on Instagram while the prominent comparison domain on Twitter is success. Inspiration is an emotion experienced most by individuals towards upward comparisons, whereas sympathy is the most experienced emotion by individuals towards downward comparisons on both Instagram and Twitter. There is no relation between social comparison level and frequency of SNS use.
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Roenneberg, Till. "Twitter as a means to study temporal behaviour." Current Biology 27, no. 17 (September 2017): R830—R832. http://dx.doi.org/10.1016/j.cub.2017.08.005.

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Johnson, Michiel, Steve Paulussen, and Peter Van Aelst. "The manifest and latent functions of Twitter use by journalists: An observational study among economic journalists." Journal of Applied Journalism & Media Studies 8, no. 3 (November 1, 2019): 311–29. http://dx.doi.org/10.1386/ajms_00004_1.

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This study focuses on Twitter use among economic journalists working for print media in Belgium. By looking into their tweeting and following behaviour, the article examines how economic journalists use Twitter for promotional, conversational and sourcing purposes. Based on an automated content analysis of what they tweet and a social network analysis of whom they follow, the results show that economic journalists mainly use Twitter to promote themselves and their news organization rather than to engage in public conversation on the platform. In addition, the study looks into their following behaviour to investigate which actors they consider as 'potential sources'. Here, the findings are consistent with previous studies among political and health journalists, indicating that journalists are more likely to follow institutionally affiliated rather than non-affiliated sources on Twitter. Furthermore, the social network analysis gives additional evidence of the media-centered of journalists' Twitter use, as media-affiliated actors maintain a dominant position in the economic journalists' Twitter networks.
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Dissertations / Theses on the topic "Twitter behaviour"

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Järpehult, Oscar, and Martin Lindblom. "Longitudinal measurements of link usage on Twitter." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-159331.

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As Twitter launched with their unique way of limiting posts to only 140 characters the usage of link shorteners was brought forth. This was the only way to fit long URLs in tweets until Twitter solved this by providing their own integrated link shortener. This study investigates how links are used on Twitter. The study include both care fulldata collection including multiple APIs and analysis of the collected data providing new insight into this topic. It was found that a small set of internet domains account for a large part of the links found in posted tweets. This set of top occurring domains did not necessarily reflect the top domains typically on common internet top lists. When looking at link shorteners in posted tweets we found that “bit.ly” was the most common one. Due to our method of collecting data we had the possibility of looking up the amount of clicks “bit.ly” links had received. We compared the click data to the amount of retweets the tweets containing these links had received and this led to some interesting discoveries regarding the ratio between these two.
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Dahlqvist, Veronica. "Why is the bird (re)tweeting? : Creating a simulation of retweeting behaviour on Twitter." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-129352.

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Social media is a big part of today’s society. But how do we know where the information we put out on the internet end up? This bachelor thesis is part of a bigger project where first year students at the cognitive science program at Linköping University will be taught about modeling of a social phenomenon. A lot can be learned about a phenomenon through modeling and simulation and that was the motivation for this bachelor thesis – to try to make a simulation of the spreading of information on social media. The social media platform that was selected was Twitter and the information spreading was narrowed down to retweeting of a tweet. The simulation was implemented in NetLogo – a modeling and simulation program. The simulation was based on important factors that contribute to a person’s willingness to retweet. The factors were found in published research reports. The result was a simulation of retweeting on Twitter that in some aspects resemble the real world phenomenon as it is depicted in published research reports. Towards the end of the report there is a discussion about what factors contributed to the resemblance or the difference between the world depicted in the published research reports and the simulation.
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Alghamdi, Bandar Abdulrahman. "Topic-based feature selection and a hybrid approach for detecting spammers on twitter." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/204112/1/Bandar%20Abdulrahman%20A_Alghamdi_Thesis.pdf.

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This thesis is an application of text mining techniques on Twitter to detect harmful users known as spam users. It examines users' posted content and characteristics to understand harmful activities and detect them. The thesis proposed methods to identify a set of new features that can accurately represent users' behavior, and also proposed a novel two-stage approach to detect spam users based on the features. The experiments conducted in the thesis work showed the effectiveness of the proposed features and the two-stage approach in detecting spam users. The thesis work made contributions to creating more safe and healthy social networks.
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Almuhanna, Nora. "Social media acceptance and use under risk : a cross-cultural study of the impact of antisocial behaviour on the use of Twitter." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/419402/.

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The problem of online antisocial behaviour is increasingly attracting public attention and is compromising the quality of online communities. Previous research into online hostility has looked at different aspects of the problem, such as definitions, classification, or specific case studies in different cyberspaces; however, the impact of antisocial behaviour on social media users remain unclear. The purpose of this research, therefore, is to investigate the impact of antisocial behaviour on social media users, specifically on Twitter (as one of the controversial cyberspaces in which antisocial behaviour is common). Furthermore, since culture plays an important role in how people use social media and interact with each other, the study investigates the impact within one western and one non-western culture, namely the Anglophone and the Saudi Arabian cultures. One approach to understanding how people use a certain technology is through technology acceptance models and theories. Hence, this study proposes a new model, called the Technology Acceptance and Use under Risk (TAUR) model, which is based on the Unified Theory of Acceptance and Use of Technology (UTAUT). The TAUR model integrates the perception of antisocial behaviour as a risk factor with other factors drawn from sociology. The model is derived from the literature and has been validated through expert reviews using semi-structured interviews. The study follows a sequential mixed methods design that gathers qualitative and quantitative data in an ordered sequence. The first phase, which included interviews with twelve experts from different disciplines, lent support to the TAUR model and inspired improvements. The second phase included a large-scale quantitative study that gathered data from 740 participants through an online questionnaire; the model was then assessed using Structural Equation Modelling (SEM) for the two different cultures. Lastly, the results were further explained through semi-structured follow-up interviews with 20 participants from both cultures. The results demonstrated that the TAUR model achieved a good fit with the data. The main finding was that the perception of antisocial behaviour does impose limitations on Twitter use, as the evidence obtained from the quantitative analysis shows that it has a negative interaction with the other factors influencing Twitter use. The subsequent qualitative analysis also supported the results by explaining how Twitter use is being restricted by perceptions of antisocial behaviour. The study also shows that performance expectancy from Twitter is a major influence on its use, despite the problem of antisocial behaviour. The research contributes to the body of knowledge in the fields of technology acceptance research, social media, and cross-cultural research theoretically, methodologically, and practically. It also demonstrates that the perceived risk of antisocial behaviour online has an effect on social media use.
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Gaillard, Béatrice. "Optimisation des stratégies de communication durant les épidémies d'arboviroses." Thesis, Montpellier 3, 2019. http://www.theses.fr/2019MON30096.

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Le fardeau des arbovirus à Aedes (comme la dengue, le chikungunya, le Zika, la fièvre jaune, etc.) s'est considérablement accru au cours des deux dernières décennies. En l'absence de vaccins (excepté pour la fièvre jaune), leur prévention et leur contrôle reposent principalement sur le contrôle des vecteurs moustiques, par le biais de stratégies intégrées de lutte antivectorielle dans lesquelles la participation collective est essentielle. Ainsi, comme le préconise l’Organisation Mondiale de la Santé qui fait de la mobilisation sociale l’un des piliers de la lutte contre les arbovirus, les plans de communication doivent être constamment optimisés.L'objectif général de cette thèse est donc d'évaluer l'influence des messages de prévention et la pertinence des nouveaux médias tels que Twitter pour optimiser les stratégies de communication afin d'influencer efficacement le comportement des populations exposées.Ce travail a été effectué dans deux zones épidémiologiques: le sud de la France, où ce risque est récent suite à l’invasion du vecteur Aedes albopictus, et la Martinique, où le moustique Aedes aegypti est implanté.Dans une première partie, nous définissons la nature du message la plus efficace au travers d’entretiens avec les populations du sud de la France et de la Martinique. Dans une deuxième partie, nous évaluons la robustesse de Twitter en tant que source de stratégies de communication en temps réel. Enfin, dans une troisième partie, nous évaluons les résultats de l’analyse des effets du chikungunya et l’expliquons, d’un point de vue sociologique.Mots-clés: réseaux sociaux, twitter, comportement humain, arboviroses, chikungunya
The burden of Aedes-borne arbovirus (ie dengue, chikungunya, Zika, yellow fever...) has increased substantially during the last two decades. In the absence of vaccine and / or curative treatment for most of these pathogens, their prevention and control are mainly based on the control of mosquitoes vectors, through integrated strategies of vector control where collective participation is pivotal. Thus, as advocated by WHO that makes social mobilization one of the pillars of the fight against arboviroses, communication plans must be constantly optimized.Therefore, the overall goal of this PhD is to evaluate the influence of prevention messages and the relevance of new media such as Twitter to optimize communication strategies to effectively influence the behavior of exposed populations. This work was carried out in two epidemiological situations: the south of France, where this risk is recent following the invasion of the potential vector Aedes albopictus, and Martinique where the mosquito Aedes aegypti is implemented since decades and can generates an habituation feeling of the inhabitants.In a first part, we aim defining the nature of the most efficient message through interviews with the populations of southern France and Martinique. In a second part, we evaluate the robustness of twitter as a source of revalant information to adapt ni real-time communication strategies. Finally, in a third part, we estimate the feelings as measured on Twitter during an outbreak of Chikungunya and explain, from a sociological point of view, how the different communication strategies performed by the authorities have impacted population feelings.Keywords: social networks, twitter, human behavior, arboviroses, chikungunya
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Mowbray, John Alexander. "The role of networking and social media tools during job search : an information behaviour perspective." Thesis, Edinburgh Napier University, 2018. http://researchrepository.napier.ac.uk/Output/1516318.

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This research reported in this thesis explores job search networking amongst 16-24 year olds living in Scotland, and the role of social media platforms (i.e. Facebook, Twitter, and LinkedIn) during this process. Networking is treated as an information behaviour; reflecting this, the study is underpinned by a prominent model from the domain of information science. A sequential, mixed methods approach was applied to gather data. This included the use of interviews, focus groups, and a survey questionnaire. The interviews incorporated ego-centric network methods to develop a relational perspective of job search networking. The findings show that young people accrue different types of information from network contacts which can be useful for all job search tasks. Indeed, frequent networking offline and on social media is associated with positive job search outcomes. This is especially true of engaging with family members and acquaintances, and frequent use of Facebook for job search purposes. However, demographic and other contextual factors have a substantial impact on the nature of networking behaviours, and the extent to which they can influence outcomes. Additionally, young jobseekers face a range of barriers to networking, do not always utilise their networks thoroughly, and are more likely to use social media platforms as supplementary tools for job search. A key contribution of this work is that it provides a detailed insight into the process of networking that has been neglected in previous studies. Its focus on social media also reveals a new dimension to the concept which has received little attention in the job search literature. Given its focus on young jobseekers living in Scotland, the findings have also been used to create a detailed list of recommendations for practitioners.
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Tran, Hung Viet. "Discovering entities' behavior through mining Twitter." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/3545.

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The unprecedented amount of user generated content from emerging social media platforms like Facebook and Twitter make them invaluable sources of information for research. Twitter in particular has about 500 million registered accounts globally who are generating approximately 340 million messages daily containing personal updates, general life observations, opinions, moods, etc. Twitter's vast amount of data, which is generally available, offers an ideal source for mining entities' behaviors. This thesis explores two research streams involving mining Twitter data. In the first work, we seek to understand the Twitter-based stakeholder communication strategies of firms. We analyze tweets posted by firms to build a system that can automatically predict target stakeholder groups of a given tweet. We also examine and incorporate firm characteristics into the system for performance improvement. The result will potentially provide valuable business intelligence to market analysts who would like to discover social media strategies and behaviors of firms. In the second work, we investigate how readers from different parts of the world react to news headlines through their Twitter messages. We design a framework for data collection, statistical analysis, sentiment analysis, and language model comparison to understand the interests and reactions of Twitter users towards news headlines. The results from this work can possibly help news organizations have better understanding of their audience for better services. Though the two research directions may seem distinct, there are points of connection. In both cases, we are interested in the impact of companies (firms and news organizations). Moreover the methods used are similar. Our results illustrate that just by gathering Twitter data stream and developing a framework to examine them, we are able to discover many interesting insights about news readers and firms.
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Nilsson, Olav, and Filip Polbratt. "Counting the clicks on Twitter : A study in understanding click behavior on Twitter." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139702.

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Social media has a large impact on our society. News articles are often accessed and shared through different social media sites . In fact, today the most common way to enter a website is from social medias. However, due to technical restrictions in what information these sites make public, it is often not possible to access click information from social medias. This complicates the analysis of popularity dynamics of news articles, for example. In this thesis, we work around that problem. By using an URL shortener service API, we can extract information about the clicks from the API. We will only look at content that is shared on Twitter because they have the friendliest view on sharing data for research purposes. To test this methodology we are doing a small prestudy in which we look at how biased news articles are shared on Twitter compared to more objective content. There are three parts in investigating the biased content. The first part is to extract Bitly links from Twitter. The second part is to examine the links and decide if it is a news article. Finally, we determine if the news article is biased. For this third step, we use two different approaches. First, we build a computational linguistics tool called a Naive Bayes classifier from already classified training data. Second, we classify different articles as articles with biased content or not, where an article is considered biased if the domain it resides on has a high content of biased articles. Our analysis of a sample data set that we have collected over a week showed that biased content is clicked for a longer period of time compared to non-biased content.
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Jeri-Yabar, Antoine, Alejandra Sanchez-Carbonel, Karen Tito, Jimena Ramirez-delCastillo, Alessandra Torres-Alcantara, Daniela Denegri, and Nilton Yhuri Carreazo. "Association between social media use (Twitter, Instagram, Facebook) and depressive symptoms: Are Twitter users at higher risk?" SAGE Publications Ltd, 2019. http://hdl.handle.net/10757/625046.

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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
Background: The purpose of this study was to determine the association between social media dependence and depressive symptoms and also, to characterize the level of dependence. It was a transversal, analytical research. Subjects and Methods: The stratified sample was 212 students from a private university that used Facebook, Instagram and/or Twitter. To measure depressive symptoms, Beck Depression Inventory was used, and to measure the dependence to social media, the Social Media Addiction Test was used, adapted from the Internet Addiction Test of Echeburúa. The collected data were subjected for analysis by descriptive statistics where STATA12 was used. Results: The results show that there is an association between social media dependence and depressive symptoms (PR [Prevalence Ratio] = 2.87, CI [Confidence Interval] 2.03–4.07). It was also shown that preferring the use of Twitter (PR = 1.84, CI 1.21–2.82) over Instagram (PR = 1.61, CI 1.13–2.28) is associated with depressive symptoms when compared to the use of Facebook. Conclusion: Excessive social media use is associated with depressive symptoms in university students, being more prominent in those who prefer the use of Twitter over Facebook and Instagram.
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Njegomir, Nicholas M. "The impact of Facebook, Twitter, and YouTube on Millennials' political behavior." Thesis, Gonzaga University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10118313.

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Social media plays a prominent role in the daily lives of Millennials. The majority of Millennials use some form of social media, and with the amount of political content on various social media sites, it is worth examining how social media influences Millennials’ political behavior. This study focused on three social media sites: Facebook, Twitter, and YouTube. This research was rooted in George Gerbner and Larry Gross’ Cultivation theory (1976), which states that long-term media exposure shapes reality. The study consisted of survey and focus group research, which attempted to determine how much time Millennials spend on each site, how politically active they are, and whether or not they thought their political behavior was influenced by social media. The resulting data showed that YouTube and Twitter were not used for political information, but Facebook is so saturated with political content that it may have a negative influence on formal political participation levels. Millennials may feel that participating in political dialogue on Facebook qualifies as formal political participation.

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Books on the topic "Twitter behaviour"

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Barnett, Mac. Billy Twitters and his big blue whale problem. New York: Disney Hyperion Books, 2009.

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Ehrenreich, Samuel E., and Marion K. Underwood. Peer Coercion and Electronic Messaging. Edited by Thomas J. Dishion and James Snyder. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199324552.013.12.

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This chapter examines how features of electronic communication (text messaging, Facebook, and Twitter) make it an ideal environment for peer influence, and how positive and negative peer reinforcement via electronic communication relates to the development and perpetuation of antisocial behavior. Electronic modes of communication allow youth to be in contact with their peer group instantaneously and continuously. The continuous access provided by electronic forms of communication may intensify the role of positive and negative reinforcement processes. Electronic communication extends youths’ ability to engage in the aversive behaviors that characterize peer coercion. This immediacy also permits less aversive, positive reinforcement processes—such as laughter and encouragement—to continue even when peers are not physically together. The role of text message communication in peer coercion and deviancy training is examined, and illustrative examples are presented. The challenges associated with measuring and observing children’s involvement with an ever-changing virtual landscape are also discussed.
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Thomason, Krista K. Ajax Reviled. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190843274.003.0006.

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Shaming punishments have increased in popularity, and social media platforms such as Twitter and Facebook have become mediums for public shaming of bad behavior. Can these practices be justified? This chapter distinguishes between three practices all labeled “shaming:” invitations to shame, shaming, and stigmatizing. It then argues that invitations to shame can be justified in certain circumstances, but shaming and stigmatizing cannot be justified. The primary argument in favor of shaming and stigmatizing is that both practices are powerful tools to change behavior. Shaming is the practice of holding up the flaws of others for public scorn, and this practice is unjustified even when it is done for noble reasons.
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Djupe, Paul A., Anand Edward Sokhey, and Amy Erica Smith. The Knowledge Polity. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780197611913.001.0001.

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The Knowledge Polity advances a holistic view of knowledge production in the social sciences. The familiar publication pipeline metaphor stresses the individual; we move beyond such a conception, offering a vision of academics as members of a knowledge polity where citizenship comes with rights and responsibilities. Knowledge production does not just mean research, but encompasses teaching, reviewing, blogging, commenting, and other activities, which together signal its communal, civic nature. Our explanation for knowledge production situates academics in institutional and social contexts, including the family, while maintaining individual agency. We search for inequalities in scholarly output, service and resources by gender and racial/ethnic identification, but are careful to consider the changing compositions of disciplines and different situations (e.g., faculty rank) when making comparisons. Data come from our Professional Activity in the Social Sciences (PASS) study, which sampled academic departments in sociology and political science in 2017. Roughly 1,700 faculty responses were linked to data on lifetime publications, Twitter activity, and Google Scholar/other data sources. Across eight empirical chapters, we offer a comprehensive view of these disciplines, documenting inequalities and providing estimates of behaviors that have long been shrouded in anecdote. The volume’s wide-ranging analyses enable scholars and academic communities from across the social and behavioral sciences to make empirically-grounded decisions about their individual and collective futures.
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Loney, Alexander C., and Stephen Scully, eds. The Oxford Handbook of Hesiod. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190209032.001.0001.

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This volume brings together twenty-nine junior and senior scholars to discuss aspects of Hesiod’s poetry and its milieu and to explore questions of reception over two and half millennia, from shortly after the poems’ conception to Twitter hashtags. Rather than an exhaustive survey of Hesiodic themes, the Handbook is conceived as a guide through terrain, some familiar, other less charted, examining both Hesiodic craft and later engagements with Hesiod’s stories of the gods and moralizing proscriptions of just human behavior. The volume is divided into four sections: “Hesiod in Context,” “Hesiod’s Art,” “Hesiod in the Greco-Roman Period,” and “Hesiod from Byzantium to Modern Times.” Topics of the chapters range from the “Hesiodic question” to the archaeology and economic history of archaic Boiotia, to Hesiod and Indo-European poetics, and from discussions of style to Hesiod’s vision of the supernatural in the Theogony, to questions of performer and audience interactions in the Works and Days. Looking at both poems together, other chapters explore tensions between diachronic and synchronic temporalities and varying portrayals of female figures. Reception studies range from Solon to comic books, with chapters in between on Hesiod and the pre-Socratics, Orphism, archaic art, Pindar, tragedy, comedy, Plato, Hellenistic poetry, Hellenistic philosophy, Virgil and the Georgic tradition, Ovid, Second Sophistic and early Christian authors in the Greco-Roman period, Byzantine and Renaissance writers and editions, Christian humanism and Milton, Enlightenment, Romanticism, and Nietzsche, Freud and structuralism, and contemporary art and literature in postclassical times.
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Nielsen, Rasmus Kleis, and Sarah Anne Ganter. The Power of Platforms. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780190908850.001.0001.

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More people today get news via Facebook and Google than via any news organization in history, and platforms like Twitter serve news to more people than all but the biggest media companies. This book draws on interviews and other data to analyze the platform power a few technology companies as a consequence have come to exercise in public life, the reservations publishers have about platforms—as well as the reasons why they often embrace them nonetheless. Most of the news content we rely on is still produced by journalists working for news organizations. But the way in which we discover it, how it is distributed, where decisions are made on what to display (and what not), and who profits from our behavior—all this is changing rapidly as people increasingly rely on social media, search engines, and aggregators offered by large platform companies to access news, and publishers in turn seek to reach people via the platforms they rely on. To understand the new, distinct relational and generative forms of power that platforms exercise, this book analyzes how they have evolved from the early days of Google’s first forays into news. Examining the different ways publishers have responded and how various platform companies have in turn handled the increasingly important and controversial role they play, it draws out the implications of a fundamental feature of our world we all need to understand: the news media are simultaneously empowered by and dependent on a few powerful private, for-profit technology companies.
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author, Shapiro-Rieser Rhonda, and Bahrami Yasmin illustrator, eds. The secret rules of social networking. AAPC Publishing, 2015.

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Book chapters on the topic "Twitter behaviour"

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Alghamdi, Bandar, Yue Xu, and Jason Watson. "Malicious Behaviour Analysis on Twitter Through the Lens of User Interest." In Communications in Computer and Information Science, 233–49. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0292-3_15.

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Narwal, Ramesh, and Himanshu Aggarwal. "Predicting Online Game-Addicted Behaviour with Sentiment Analysis Using Twitter Data." In Lecture Notes in Electrical Engineering, 505–17. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2354-7_45.

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Weiss, Fernanda, Ignacio Espinoza, Julio Hurtado, and Marcelo Mendoza. "Claim Behavior over Time in Twitter." In Social Computing and Social Media. Design, Human Behavior and Analytics, 468–79. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21902-4_33.

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Guo, Lixiang, Zhaoyun Ding, and Hui Wang. "Behavior-Based Twitter Overlapping Community Detection." In Database Systems for Advanced Applications, 371–76. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32055-7_31.

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Dhall, Abhinav, and Jesse Hoey. "First Impressions - Predicting User Personality from Twitter Profile Images." In Human Behavior Understanding, 148–58. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46843-3_10.

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Cagliero, Luca, and Alessandro Fiori. "Analyzing Twitter User Behaviors and Topic Trends by Exploiting Dynamic Rules." In Behavior Computing, 267–87. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2969-1_17.

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Sung, Juyup, Seunghyeon Moon, and Jae-Gil Lee. "The Influence in Twitter: Are They Really Influenced?" In Behavior and Social Computing, 95–105. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-04048-6_9.

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Malave, Nitin, and Sudhir N. Dhage. "Sarcasm Detection on Twitter: User Behavior Approach." In Intelligent Systems, Technologies and Applications, 65–76. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6095-4_5.

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Hayama, Tessai. "Detecting TV Program Highlight Scenes Using Twitter Data Classified by Twitter User Behavior." In Recent Advances and Future Prospects in Knowledge, Information and Creativity Support Systems, 1–13. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70019-9_1.

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Qi, SiHua, Lulwah AlKulaib, and David A. Broniatowski. "Detecting and Characterizing Bot-Like Behavior on Twitter." In Social, Cultural, and Behavioral Modeling, 228–32. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93372-6_26.

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Conference papers on the topic "Twitter behaviour"

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Orozco, Albert, Sacha Levy, and Reihaneh Rabbany. "Graph Neural Networks Learn Twitter Bot Behaviour." In LatinX in AI at Neural Information Processing Systems Conference 2020. Journal of LatinX in AI Research, 2020. http://dx.doi.org/10.52591/lxai2020121213.

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Social media trends are increasingly taking a significant role for the understanding of modern social dynamics. In this work, we take a look at how the Twitter landscape gets constantly shaped by automatically generated content. Twitter bot activity can be traced via network abstractions which, we hypothesize, can be learned through state-of-the-art graph neural network techniques. We employ a large bot database, continuously updated by Twitter, to learn how likely is that a user is mentioned by a bot, as well as, for a hashtag. Thus, we model this likelihood as a link prediction task between the set of users and hashtags. Moreover, we contrast our results by performing similar experiments on a crawled data set of real users.
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Kekulluoglu, Dilara, Kami Vaniea, and Walid Magdy. "Understanding Privacy Switching Behaviour on Twitter." In CHI '22: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3491102.3517675.

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Bello, Bello Shehu, Reiko Heckel, and Leandro Minku. "Reverse Engineering the Behaviour of Twitter Bots." In 2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS). IEEE, 2018. http://dx.doi.org/10.1109/snams.2018.8554675.

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Khazaei, Taraneh, Lu Xiao, Robert Mercer, and Atif Khan. "Privacy Behaviour and Profile Configuration in Twitter." In the 25th International Conference Companion. New York, New York, USA: ACM Press, 2016. http://dx.doi.org/10.1145/2872518.2890088.

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Bello, Bello Shehu, and Reiko Heckel. "Analyzing the Behaviour of Twitter Bots in Post Brexit Politics." In 2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS). IEEE, 2019. http://dx.doi.org/10.1109/snams.2019.8931874.

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Blanco-Herrero, David, Patricia Sánchez-Holgado, Javier J. Amores, Maximiliano Frías-Vázquez, and Carlos Arcila-Calderón. "News media behaviour in Twitter during a major political event." In TEEM'20: Eighth International Conference on Technological Ecosystems for Enhancing Multiculturality. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3434780.3436674.

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Perez Cabañero, Carmen, Enrique Bigne, Carla Ruiz Mafe, and Antonio Carlos Cuenca. "Sentiment Analysis of Twitter in Tourism Destinations." In CARMA 2020 - 3rd International Conference on Advanced Research Methods and Analytics. Valencia: Universitat Politècnica de València, 2020. http://dx.doi.org/10.4995/carma2020.2020.11621.

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Given the importance of electronic word of mouth (eWOM), this paperanalyses the content of messages generated by users related to a touristdestination and shared through Twitter. We propose three research questionsregarding eWOM behaviour in Twitter focused on the expertise of thereviewer, sentiment analysis of a tweet and its content. In order to addressthose research questions we carry out text mining analysis by retrievingexisting information on Twitter (over 1500 tweets) regarding to Venice as atourist destination.
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Featherstone, Coral. "South African bot behaviour post the July 2018 Twitter account cull." In 2019 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD). IEEE, 2019. http://dx.doi.org/10.1109/icabcd.2019.8851039.

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El Houda Ben Chaabene, Nour, Amel Bouzeghoub, Ramzi Guetari, and Henda Hajjami Ben Ghezala. "Applying Machine Learning Models for Detecting and Predicting Militant Terrorists Behaviour in Twitter." In 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2021. http://dx.doi.org/10.1109/smc52423.2021.9659253.

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Guimarães, Nuno, Álvaro Figueira, and Luís Torgo. "Contributions to the Detection of Unreliable Twitter Accounts through Analysis of Content and Behaviour." In 10th International Conference on Knowledge Discovery and Information Retrieval. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006932800920101.

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