Identifying interesting Twitter contents using topical analysis

Social media platforms such as Twitter are becoming increasingly mainstream which provides valuable user-generated information by publishing and sharing contents. Identifying interesting and useful contents from large text-streams is a crucial issue in social media because many users struggle with information overload. Retweeting as a forwarding function plays an important role in information propagation where the retweet counts simply reflect a tweet’s popularity. However, the main reason for retweets may be limited to personal interests and satisfactions. In this paper, we use a topic identification as a proxy to understand a large number of tweets and to score the interestingness of an individual tweet based on its latent topics. Our assumption is that fascinating topics generate contents that may be of potential interest to a wide audience. We propose a novel topic model called Trend Sensitive-Latent Dirichlet Allocation (TS-LDA) that can efficiently extract latent topics from contents by modeling temporal trends on Twitter over time. The experimental results on real world data from Twitter demonstrate that our proposed method outperforms several other baseline methods.     

Celebrity's self-disclosure on Twitter and parasocial relationships: A mediating role of social presence

This study investigated how celebrities' self-disclosure on personal social media accounts, particularly Twitter, affects fans' perceptions. An online survey was utilized among a sample of 429 celebrity followers on Twitter. Results demonstrated that celebrities' professional self-disclosure (e.g., sharing their work-related life), personal self-disclosure (e.g., sharing their personal life such as friends and family), and fans' retweeting behavior, enhanced fans’ feeling of social presence, thereby positively affecting parasocial interaction with celebrities. Further, the study found that the effects of self-disclosure and retweeting on parasocial interaction were mediated by social presence. Implications and future research directions are provided.     

Tweet this: A uses and gratifications perspective on how active Twitter use gratifies a need to connect with others

Twitter is an Internet social-network and micro-blogging platform with both mass and interpersonal communication features for sharing 140-character messages, called tweets, with other people, called followers. Hierarchical OLS regression of survey results from 317 Twitter users found that the more months a person is active on Twitter and the more hours per week the person spends on Twitter, the more the person gratifies a need for an informal sense of camaraderie, called connection, with other users. Controlling for demographic variables does not diminish this positive relationship. Additionally, frequency of tweeting and number of @replies, public messages between Twitter users, mediate the relationship between active Twitter use and gratifying a need for connection. Results are discussed in light of uses and gratifications theory.     

A network analysis of official Twitter accounts during the West Virginia water crisis

Online networks using Web 2.0 technologies have proven useful for communication among all parties involved in managing crises. These networks rapidly disseminate information allowing for coordination among organizations responding to the needs of those whose safety and wellbeing are threatened by the crisis and its aftermath. This study provides a network analysis of official Twitter accounts activated during the Charleston, West Virginia, water contamination crisis in 2014. The city’s water supply was rendered unfit for drinking or bathing after 7500 gallons of a toxic chemical leaked into the Elk River. The network created by the 41 Twitter accounts associated with the West Virginia water contamination lacked density, contained several isolates, exchanged information quickly (geodesic distance diameter), and contained both national and local accounts. The lack of density indicates limited exchange of information, particularly between national and federal accounts. The rapid dissemination of the information that was shared and the fact that some accounts did bridge the local and national gap, however, show the positive potential for such networks in responding to crises.     

‘Breaking’ news: uncovering sense-breaking patterns in social media crisis communication during the 2017 Manchester bombing

ABSTRACT

Individuals, (media-) organisations, and crisis responders who are involved in ad hoc crisis communication steadily deploy social media to contribute to collective sense-making as an endeavour to create meaning in highly uncertain situations. Exerting sense-giving in order to shape others’ conceptions is causally preceded by an initial breakup of existing understanding. This study aims to explore patterns of sense-breaking in social media crisis communication and its impact on collective sense-making and sense-giving. To this end, we conducted a case study of the Manchester bombing in 2017, including a social network analysis of 708,147 Twitter postings and a content analysis of 2006 original tweets. We found individual role types to be initiators of sense-breaking in early crisis stages when uncertainty is at its height. Exerting successive sense-giving becomes more challenging if the collective sense-making has progressed along with the sequence of events. This understanding aims to encourage emergency management organisations to move their sense-giving actions closer to the point in time when sense-breaking occurs.     

Experiencing motivational conflict on social media in a crisis situation: The case of the Chick-fil-A same-sex marriage controversy

This study examined the relationship between motivational conflict involving social media use and attitude formation in a brand crisis situation. An online experiment was conducted with 658 participants using a 2 (news-article valence: positive vs. negative) × 2 (situational cue valence: positive vs. negative) between-subjects design. During the experiment, participants loyal to Chick-fil-A (defense-motivated) were asked to communicate the brand through the brand's social networking sites (SNSs) while receiving a cue for the SNS audience's general unfavorable opinions on the crisis issue, the Chick-fil-A same-sex marriage controversy (impression-motivated). It was found that when motivational conflict was experienced (defense vs. impression), (1) individuals' brand attitudes were affected more by objective information such as a news article than by a cue for audience opinion and (2) their positive brand-related cognitions were countervailed by their impression-related cognitions. Overall, the findings suggest that it is not always desirable for a company to encourage customers to engage in SNS-facilitated interaction in a crisis situation.     

Urban Social Media Demographics: An Exploration of Twitter Use in Major American Cities

This article explores intersections between place, race/ethnicity, and gender amongst American Twitter users and makes an argument that studying the intensity of tweets provides insights into how and why particular groups tweet. Given recent events in American political life such as the shooting in Ferguson, Missouri and the reactions by young, urban African Americans on Twitter, understanding the role of race, place, gender, and age is important. We observed the time between tweets of urban American Twitter users and explored whether the medium may be providing traditionally marginalized groups, such as young Black men, with potential avenues for mobilizing communication and access to resources.     

Exploring extreme events on social media: A comparison of user reposting/retweeting behaviors on Twitter and Weibo

Although recent research suggests that Twitter and other forms of micro-blogging are becoming increasingly relied upon by both the public and response agencies dealing with crises and disasters, little is known about how these dynamics may play out in a non-Western context. The current study examines the use of the Chinese Weibo service during a 2013 smog emergency, and compares user generated content to that found in earlier data concerning a weather event in North America. The results indicate that by way of comparison, the Weibo sample contained proportionately similar degrees of informative and affective content, but that users were less likely to use humor and showed no increase in affective outpouring as the crisis developed. Results are discussed in terms of implications for those designing social media campaigns for informing and motivating those affected by large-scale weather-related crises.     

Antecedents and consequences of trust in a social media brand: A cross-cultural study of Twitter

This study extends brand relationship theory to the context of the microblogging platform Twitter. The authors investigate the impact of Twitter trust on users’ intentions to continue using the platform and to “follow” brands that are hosted on Twitter (the trust transfer phenomenon). They also explore the role of perceived self-Twitter personality match in strengthening trust towards the Twitter brand. A cross-cultural American–Ukrainian sample allows to identify potential culture-based differences in brand personality and brand trust concepts. The results show that the positive effect of trust in Twitter on its users’ patronage intentions is robust across two cultures with diverse history and ideology. An important novel finding is the influence of trust in Twitter on patronage intentions towards the businesses hosted on Twitter. However, this relationship reaches statistical significance only in the Ukrainian sample, signaling potential differences in the trust transfer processes in different cultures. The study confirms the role of similarity in personality traits between Twitter users and the Twitter brand in engendering trust in Twitter. The salience of different personality traits in the “personality match – Twitter trust” link for different cultures suggests important implications for global marketers.     

Excessive use of Twitter among college students in the UK: Validation of the Microblog Excessive Use Scale and relationship to social interaction and loneliness

Microblogging on sites like Twitter is a growing and popular trend among young people. Apparently, some users of these microblogs exhibit addiction-like symptoms. Until recently, there was no psychometric scale to measure the excessive use of Twitter. The development of the Microblog Excessive Use Scale (MEUS) in 2014 proved a positive step in assessing this phenomenon. In the current study, we employed the MEUS to assess excessive use of Twitter in a sample of 256 college students (53.1% female; mean age 21.4 years) in the UK. Confirmatory factor analysis (CFA), calculation of criterion-related and concurrent validity and reliability were performed to assess the scale's psychometric properties. The MEUS was found to be a valid instrument for assessing excessive use of Twitter among UK college students. In addition, we found that real life social interaction was negatively associated with excessive use of Twitter and this relationship was mediated by loneliness. We compared our results with results from a previous study in which the MEUS was developed and noted some interesting differences, which might be explained by cultural differences between samples in the two studies.     

An evaluation of the run-time and task-based performance of event detection techniques for Twitter

Twitter׳s increasing popularity as a source of up-to-date news and information about current events has spawned a body of research on event detection techniques for social media data streams. Although all proposed approaches provide some evidence as to the quality of the detected events, none relate this task-based performance to their run-time performance in terms of processing speed, data throughput, or memory usage. In particular, neither a quantitative nor a comparative evaluation of these aspects has been performed to date. In this article, we study the run-time and task-based performance of several state-of-the-art event detection techniques for Twitter. In order to reproducibly compare run-time performance, our approach is based on a general-purpose data stream management system, whereas task-based performance is automatically assessed based on a series of novel measures.     

A simplistic model for identifying prominent web users in directed multiplex social networks: a case study using Twitter networks

This paper aims to describe a new simplistic model dedicated to gauge the online influence of Twitter users based on a mixture of structural and interactional features. The model is an additive mathematical formulation which involves two main parts. The first part serves to measure the influence of the Twitter user on just his neighbourhood covering his followers. However, the second part evaluates the potential influence of the Twitter user beyond the circle of his followers. Particularly, it measures the likelihood that the tweets of the Twitter user will spread further within the social graph through the retweeting process. The model is tested on a data set involving four kinds of real-world egocentric networks. The empirical results reveal that an active ordinary user is more prominent than a non-active celebrity one. A simple comparison is conducted between the proposed model and two existing simplistic approaches. The results show that our model generates the most realistic influence scores due to its dealing with both explicit (structural and interactional) and implicit features.     

Facebook,Twitter, & Qr codes: An exploratory trial examining the feasibility of social media mechanisms for sample recruitment

This study examined the effectiveness of three social media based recruitment channels for sampling rural adolescent populations for online health research. At present, there is no consensus on the optimal social media based vehicle for recruiting adolescents due to limited research. This exploratory study compared Facebook ads, Twitter, and QR code postcards at three different but demographically similar rural high schools. The results showed that QR codes had the highest response percentage and the lowest cost per recruited participant, whereas Twitter had the lowest response percentage and Facebook had the highest cost per recruited participant. Although this is the first time QR codes were examined in this context, it seemed to show potential in online health research. The findings are interpreted from a variety of theoretical and conceptual frameworks. Applications of each recruitment channel are discussed and suggestions are provided for future research.     

A Survey of Techniques for Event Detection in Twitter

Twitter is among the fastest‐growing microblogging and online social networking services. Messages posted on Twitter (tweets) have been reporting everything from daily life stories to the latest local and global news and events. Monitoring and analyzing this rich and continuous user‐generated content can yield unprecedentedly valuable information, enabling users and organizations to acquire actionable knowledge. This article provides a survey of techniques for event detection from Twitter streams. These techniques aim at finding real‐world occurrences that unfold over space and time. In contrast to conventional media, event detection from Twitter streams poses new challenges. Twitter streams contain large amounts of meaningless messages and polluted content, which negatively affect the detection performance. In addition, traditional text mining techniques are not suitable, because of the short length of tweets, the large number of spelling and grammatical errors, and the frequent use of informal and mixed language. Event detection techniques presented in literature address these issues by adapting techniques from various fields to the uniqueness of Twitter. This article classifies these techniques according to the event type, detection task, and detection method and discusses commonly used features. Finally, it highlights the need for public benchmarks to evaluate the performance of different detection approaches and various features.     

Twitter versus Facebook: Exploring the role of narcissism in the motives and usage of different social media platforms

The amount of research on social networking sites (SNS) and narcissism is accumulating quickly requiring greater levels of variable specification and more fine-tuned hypothesis testing to clearly determine the relationships among key variables. The current investigation examines two of the most popular SNS, Facebook and Twitter, formulating hypotheses around the specific features of each site within college and adult samples. Unlike previous research that has focused almost exclusively on SNS usage, we focused on active usage (i.e., SNS content generation) as opposed to passive usage (i.e., SNS consumption) and included reasons for usage as a potential black box in the narcissism to SNS usage relationship. Results suggest that the features of Twitter make tweeting the preferred means of active usage among narcissists in the college sample, but not the adult sample, who prefer Facebook. In fact, we found no significant direct or indirect relationship with active usage on Facebook for the college sample, calling into question popular press articles linking Millennial narcissism with Facebook use. Additionally platform differences (i.e., microblogging versus profile-based) may explain the importance of active usage on Twitter relative to Facebook. That is, with Twitter, narcissistic motives for usage all manifest through tweeting while Facebook provides other mechanisms to achieve narcissistic motives.     

Attention to news and its dissemination on Twitter: A survey

In recent years, news media have been hugely disrupted by news promotion, commentary and sharing in online, social media (e.g., Twitter, Facebook, and Reddit). This disruption has been the subject of a significant literature that has largely used AI techniques – machine learning, text analytics and network models – to both (i) understand the factors underlying audience attention and news dissemination on social media (e.g., effects of popularity, type of day) and (ii) provide new tools/guidelines for journalists to better disseminate their news via these social media. This paper provides an integrative review of the literature on the professional reporting of news on Twitter; focusing on how journalists and news outlets use Twitter as a platform to disseminate news, and on the factors that impact readers’ attention and engagement with that news on Twitter. Using the precise definition of a news-tweet (i.e., divided into user, content and context features), the survey structures the literature to reveal the main findings on features affecting audience attention to news and its dissemination on Twitter. From this analysis, it then considers the most effective guidelines for digital journalists to better disseminate news in the future.     

Birds of a Feather Tweet Together: Integrating Network and Content Analyses to Examine Cross‐Ideology Exposure on Twitter

This study integrates network and content analyses to examine exposure to cross‐ideological political views on Twitter. We mapped the Twitter networks of 10 controversial political topics, discovered clusters – subgroups of highly self‐connected users – and coded messages and links in them for political orientation. We found that Twitter users are unlikely to be exposed to cross‐ideological content from the clusters of users they followed, as these were usually politically homogeneous. Links pointed at grassroots web pages (e.g.: blogs) more frequently than traditional media websites. Liberal messages, however, were more likely to link to traditional media. Last, we found that more specific topics of controversy had both conservative and liberal clusters, while in broader topics, dominant clusters reflected conservative sentiment.     

The Rise of Twitter in the Political Campaign: Searching for Intermedia Agenda‐Setting Effects in the Presidential Primary

Questions exist over the extent to which social media content may bypass, follow, or attract the attention of traditional media. This study sheds light on such dynamics by examining intermedia agenda‐setting effects among the Twitter feeds of the 2012 presidential primary candidates, Twitter feeds of the Republican and Democratic parties, and articles published in the nation's top newspapers. Daily issue frequencies within media were analyzed using time series analysis. A symbiotic relationship was found between agendas in Twitter posts and traditional news, with varying levels of intensity and differential time lags by issue. While traditional media follow candidates on certain topics, on others they are able to predict the political agenda on Twitter.     

Structure of Ego‐Alter Relationships of Politicians in Twitter

We analyze the ego‐alter Twitter networks of 300 Italian MPs and 18 European leaders, and of about 14,000 generic users. We find structural properties typical of social environments, meaning that Twitter activity is controlled by constraints that are similar to those shaping conventional social relationships. However, the evolution of ego‐alter ties is very dynamic, which suggests that they are not entirely used for social interaction, but for public signaling and self‐promotion. From this standpoint, the behavior of EU leaders is much more evident, while Italian MPs are in between them and generic users. We find that politicians – more than generic users – create relationships as a side effect of tweeting on discussion topics, rather than by contacting specific alters.