Tai Quan Peng

Visual Analysis of Topic Competition on Social Media

How do various topics compete for public attention when they are spreading on social media? What roles do opinion leaders play in the rise and fall of competitiveness of various topics? In this study, we propose an expanded topic competition model to characterize the competition for public attention on multiple topics promoted by various opinion leaders on social media. To allow an intuitive understanding of the estimated measures, we present a timeline visualization through a metaphoric interpretation of the results. The visual design features both topical and social aspects of the information diffusion process by compositing ThemeRiver with storyline style visualization. ThemeRiver shows the increase and decrease of competitiveness of each topic. Opinion leaders are drawn as threads that converge or diverge with regard to their roles in influencing the public agenda change over time. To validate the effectiveness of the visual analysis techniques, we report the insights gained on two collections of Tweets: the 2012 United States presidential election and the Occupy Wall Street movement.

EvoRiver: Visual Analysis of Topic Coopetition on Social Media.

Cooperation and competition (jointly called “coopetition”) are two modes of interactions among a set of concurrent topics on social media. How do topics cooperate or compete with each other to gain public attention? Which topics tend to cooperate or compete with one another? Who plays the key role in coopetition-related interactions? We answer these intricate questions by proposing a visual analytics system that facilitates the in-depth analysis of topic coopetition on social media. We model the complex interactions among topics as a combination of carry-over, coopetition recruitment, and coopetition distraction effects. This model provides a close functional approximation of the coopetition process by depicting how different groups of influential users (i.e., “topic leaders”) affect coopetition. We also design EvoRiver, a time-based visualization, that allows users to explore coopetition-related interactions and to detect dynamically evolving patterns, as well as their major causes. We test our model and demonstrate the usefulness of our system based on two Twitter data sets (social topics data and business topics data).

Mapping the landscape of Internet studies: Text mining of social science journal articles 2000–2009

What does ‘Internet studies’ entail as a field of social science research? We aim to answer the question by mapping research themes, theorization, and methodology of Internet studies based on 27,000+ articles published in Social Sciences Citation Index and Arts & Humanities Citation Index journals over the last 10 years. In analyzing the articles, we adopt a ‘bottom-up’ approach – classifying keywords of the Internet studies without any a priori categorization – to identify the boundaries, major divisions, and basic elements of the field talis qualis. The research strategy results in a number of expected, as well as surprising, patterns and trends. Internet studies have evolved into a viable field that has witnessed a booming decade. The field is clustered around four primary research themes: e-Health, e-Business, e-Society, and Human–Technology Interactions. Two or three sub-themes with different research foci and methodologies emerge within each theme. The evolution of popular keywords in each sub-theme further shows that the field has become more concerned with intricate relationships between Internet use and specific behaviors/attitudes/effects; Internet usage patterns have increasingly attracted research attention; and network perspectives and approaches have become popular. Internet studies in the past decade have been modestly theorized. Established research methods (e.g., survey, experiment, and content analysis) still prevail in the Internet studies reviewed.

Where you publish matters most: A multilevel analysis of factors affecting citations of internet studies

This study explores the factors influencing citations to Internet studies by assessing the relative explanatory power of three perspectives: normative theory, the social constructivist approach, and a natural growth mechanism. Using data on 7,700+ articles of Internet studies published in 100+ Social Sciences Citation Index (SSCI)-listed journals in 2000–2009, the study adopted a multilevel model to disentangle the impact between article- and journal-level factors on citations. This research strategy resulted in a number of both expected and surprising findings. The primary determinants for citations are found to be journal-level factors, accounting for 14% of the variances in citations of Internet studies. The impact of some, if not all, article-level factors on citations are moderated by journal-level factors. Internet studies, like studies in other areas (e.g., management, demography, and ecology), are cited more for rhetorical purposes, as suggested by the social constructivist approach, rather than as a form of reward, as argued by normative theory. The impact of time on citations varies across journals, which creates a growing “citation gap” for Internet studies published in journals with different characteristics.

Follower-Followee Network, Communication Networks, and Vote Agreement of the U.S. Members of Congress

The digital traces of U.S. members of congress on Twitter enable researchers to observe how these public officials interact with one another in a direct and unobtrusive manner. Using data from Twitter and other sources (e.g., roll-call vote data), this study aims to examine how members of congress connect and communicate with one another on Twitter, why they will connect and communicate with one another in such a way, and what effects such connection and communication among members of congress have on their floor vote behavior. The follower-followee and communication networks of members of congress on Twitter demonstrate a high degree of partisan homogeneity. Members of congress prefer to follow or communicate with other members who are similar to them in terms of partisanship, home state, chamber, and public concern. This condition is known as the homophily effect in social network research. However, the magnitude of the homophily effect is mitigated when the effects of endogenous networking mechanisms (i.e., reciprocity and triadic closure) in such networks are controlled. Follower-followee ties can facilitate political discourse among members of congress on Twitter, whereas both follower-followee and communication ties on Twitter increase the likelihood of vote agreement among members of congress. The theoretical, methodological, and practical implications of the findings are addressed.

Breadth, depth, and speed: diffusion of advertising messages on microblogging sites

Purpose – The purpose of this paper is to present an empirical assessment of the diffusion of advertising messages on microblogging sites. The diffusion properties of advertising messages are quantified based on the following three aspects: diffusion breadth, depth, and speed. Furthermore, this study examines the influence of message- and advertiser-level factors on the diffusion of advertising messages. Design/methodology/approach – The study data comprises 20,000 advertising messages that are randomly drawn from a popular microblogging web site in China. Five message-level factors and four advertiser-level factors are constructed based on the information retrieved from the microblogging web site. Generalized linear modeling is adopted to examine the effects of such factors on the diffusion properties of advertising messages. Findings – The positive driving forces underlying the diffusion of advertising messages on microblogging sites include message length, the advertisers’ in-degrees, and their reputat...

The divided communities of shared concerns: Mapping the intellectual structure of e-Health research in social science journals

PURPOSE Social scientific approach has become an important approach in e-Health studies over the past decade. However, there has been little systematical examination of what aspects of e-Health social scientists have studied and how relevant and informative knowledge has been produced and diffused by this line of inquiry. This study performed a systematic review of the body of e-Health literature in mainstream social science journals over the past decade by testing the applicability of a 5A categorization (i.e., access, availability, appropriateness, acceptability, and applicability), proposed by the U.S. Department of Health and Human Services, as a framework for understanding social scientific research in e-Health. METHODS This study used a quantitative, bottom-up approach to review the e-Health literature in social sciences published from 2000 to 2009. A total of 3005 e-Health studies identified from two social sciences databases (i.e., Social Sciences Citation Index and Arts & Humanities Citation Index) were analyzed with text topic modeling and structural analysis of co-word network, co-citation network, and scientific food web. RESULTS There have been dramatic increases in the scale of e-Health studies in social sciences over the past decade in terms of the numbers of publications, journal outlets and participating disciplines. The results empirically confirm the presence of the 5A clusters in e-Health research, with the cluster of applicability as the dominant research area and the cluster of availability as the major knowledge producer for other clusters. The network analysis also reveals that the five distinctive clusters share much more in common in research concerns than what e-Health scholars appear to recognize. CONCLUSIONS It is time to explicate and, more importantly, tap into the shared concerns cutting across the seemingly divided scholarly communities. In particular, more synergy exercises are needed to promote adherence of the field.

A Game of Win-Win or Win-Lose? Revisiting the Internet’s Influence on Sociability and Use of Traditional Media

This study examines the influence of internet adoption and internet usage on sociability and use of traditional media. With empirical data collected in Hong Kong between 2003 and 2005, it confirms that adoption and usage are two distinct processes, with different social impacts. It is found that, on average, internet users spend significantly less time on traditional media than nonusers, while both groups spend the same amount of time on social activities. Furthermore, users’ sociability and use of traditional media are positively correlated with each other, while among nonusers there is no such correlation. When the spotlight is turned on internet users, a new measurement, called ‘sophistication of internet usage’, is employed to examine the impact of internet use on traditional media use and sociability. It is found in the study that internet use does not influence users’ sociability and use of traditional media, regardless of the length of internet adoption history, which disconfirms the so-called ‘novelty effect’.

How ideas flow across multiple social groups

Tracking how correlated ideas flow within and across multiple social groups facilitates the understanding of the transfer of information, opinions, and thoughts on social media. In this paper, we present IdeaFlow, a visual analytics system for analyzing the lead-lag changes within and across pre-defined social groups regarding a specific set of correlated ideas, each of which is described by a set of words. To model idea flows accurately, we develop a random-walk-based correlation model and integrate it with Bayesian conditional cointegration and a tensor-based technique. To convey complex lead-lag relationships over time, IdeaFlow combines the strengths of a bubble tree, a flow map, and a timeline. In particular, we develop a Voronoi-treemap-based bubble tree to help users get an overview of a set of ideas quickly. A correlated-clustering-based layout algorithm is used to simultaneously generate multiple flow maps with less ambiguity. We also introduce a focus+context timeline to explore huge amounts of temporal data at different levels of time granularity. Quantitative evaluation and case studies demonstrate the accuracy and effectiveness of IdeaFlow.

Network closure, brokerage, and structural influence of journals: a longitudinal study of journal citation network in Internet research (2000---2010)

The study aims to assess journals’ structural influence in Internet research and uncover the impacts of network structures on journals’ structural influence drawing on theories of network closure and structural holes. The data of the study are the citation exchanges among 1,210 journals in Communication and other seven social scientific fields (i.e., Business, Economics/Finance, Education, Information Science, Political Science, Psychology, and Sociology) in Internet research. The top two most influential journals in Internet research are American Economic Review and Journal of Personality and Social Psychology. Journals in “Communication” field emerge to be an important source of influence in Internet research, whose mean structural influence ranks third among the eight fields, below “Business” and “Economics/Finance”, but above other five fields. Journals’ structural influences are found to grow over time and the growth rates vary across journals. Network brokerage is found to exert a significant impact on journals’ structural influence, while the impact of network closure on journals’ structural influences is not significant. The impact of network brokerage on journals’ structural influence will increase over time.