The emerging viewertariat in South Korea: The Seoul mayoral TV debate on Twitter, Facebook, and blogs

Heo, Yun-Cheol; Park, JiYoung; Kim, Jiyoung Ydun; Park, Han Woo

doi:10.1016/j.tele.2015.08.003

Cited by 15 publications

(14 citation statements)

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“…Twitter's role in political communication in different parts of the world, especially around elections and campaigning, has increasingly been studied in recent years (Weller et al, 2014). Such studies have generally examined the use of Twitter as a communication channel for social protests (Penney and Dadas, 2014), political election campaigns (Enli, 2017;Heo et al, 2016;Jungherr, 2016;Jungherr et al, 2015;Kim et al, 2016;McGregor, 2018;Ott, 2017;Park et al, 2016), and revolutionary movements during political upheavals (Lotan et al, 2011). In these contexts, Twitter has been used either by politicians (parties and candidates) as a platform for self-representation, or by citizens or ''Twitter publics'' (Jungherr, 2016), as a communication tool for arranging social and political movements (Anstead and Chadwick, 2018;Ceron, 2017;Engesser et al, 2017).…”

Section: Twitter As a Medium For Political Communicationmentioning

confidence: 99%

Mapping the political landscape of Persian Twitter: The case of 2013 presidential election

Khazraee

2019

Big Data & Society

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The fallacy of premature designations such as “Iran's Twitter Revolution” can be attributed to the empirical gap in our knowledge about such sociotechnical phenomena in non-Western societies. To fill this gap, we need in-depth analyses of social media use in those contexts and to create detailed maps of online public environments in such societies. This paper aims to present such cartography of the political landscape of Persian Twitter by studying the case of Iran's 2013 presidential election. The objective of this study is twofold: first, to fill the empirical gap in our knowledge about Twitter use in Iran, and second, to develop computational methods for studying Persian Twitter (e.g., effective methods for analyzing Persian text) and identify the best methods for addressing different issues (e.g., topic detection and sentiment analysis). During Iran's 2013 presidential election, three million tweets were collected and analyzed using social network analysis and machine learning. The findings provide a more nuanced view of the political landscape of Persian Twitter and identify patterns in accordance with or in contrast to those identified in the English-speaking Twittersphere around the 2013 presidential election. Persian Twitter was dominated by micro-celebrities, whereas institutional elites dominated English discourse about Iran on Twitter. The results also illustrate that Persian Twitter in 2013 was predominantly in favor of reformists. Finally, this study demonstrates that sentiment analysis toward political name entities can be used efficiently for mapping the political landscape of conversation on Twitter.

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Section: Twitter As a Medium For Political Communicationmentioning

confidence: 99%

Mapping the political landscape of Persian Twitter: The case of 2013 presidential election

Khazraee

2019

Big Data & Society

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“…For example, prior studies examine semantic networks based on co-occurrence of words in various social media posts (Kim, Heo, Choi, & Park, 2014;Shapiro & Park, 2015;Xu et al, 2015Xu et al, , 2016Park, Lim, & Park, 2015). Co-occurrence of words can reveal thematic/topic similarity and variation in online public discussions of issues (Heo, Park, Kim, & Park, 2016), or the media's framing of international events (Jiang, Barnett, & Taylor, 2016). In the current study, a network of nations based on co-occurrence reflects how the public perceives the connection between two given countries in a semantic context.…”

Section: Applying Network Analysis To International Relationsmentioning

confidence: 99%

Measuring international relations in social media conversations

Barnett

Chu

et al. 2017

Government Information Quarterly

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a b s t r a c t a r t i c l e i n f oThis paper examines international relations as perceived by the public in their social media conversations. It examines over 1.8 billion Facebook postings in English and 51 million Chinese posts on Weibo, to reveal the relations among nations as expressed in social media conversations. It argues that social media represent a transnational electronic public sphere, in which public discussions reveal characteristics of international relations as perceived by a foreign public. The findings show that the international relations in social media postings match the core-peripheral structure proposed in the World Systems Theory. Additionally, the relations are associated with the amount of news coverage and public attention a country receives. Overall, the study demonstrates the value of webometric data in revealing how international relations are perceived by average citizens.

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“…Compared with face-to-face interventions, web-based delivery of social media offers advantages such as continuous availability and remote access, which could reduce barriers to intervention use among participants of low SES, such as limited time or inadequate transportation [9,10]. In addition, social media users are accustomed to sharing information about their health experiences and opinions [11,12]. This sharing may be enhanced by the communication features of social media websites, which can facilitate sharing and communication among users about weight loss behaviors, goals, and experiences [13,14].…”

Section: Introductionmentioning

confidence: 99%

Social Network Analysis of the Effects of a Social Media–Based Weight Loss Intervention Targeting Adults of Low Socioeconomic Status: Single-Arm Intervention Trial

Xu¹,

Cavallo²

2021

J Med Internet Res

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Background Obesity is a known risk factor for cardiovascular disease risk factors, including hypertension and type II diabetes. Although numerous weight loss interventions have demonstrated efficacy, there is considerably less evidence about the theoretical mechanisms through which they work. Delivering lifestyle behavior change interventions via social media provides unique opportunities for understanding mechanisms of intervention effects. Server data collected directly from web-based platforms can provide detailed, real-time behavioral information over the course of intervention programs that can be used to understand how interventions work. Objective The objective of this study was to demonstrate how social network analysis can facilitate our understanding of the mechanisms underlying a social media–based weight loss intervention. Methods We performed secondary analysis by using data from a pilot study that delivered a dietary and physical activity intervention to a group of participants via Facebook. We mapped out participants’ interaction networks over the 12-week intervention period and linked participants’ network characteristics (eg, in-degree, out-degree, network constraint) to participants’ changes in theoretical mediators (ie, dietary knowledge, perceived social support, self-efficacy) and weight loss by using regression analysis. We also performed mediation analyses to explore how the effects of social network measures on weight loss could be mediated by the aforementioned theoretical mediators. Results In this analysis, 47 participants from 2 waves completed the study and were included. We found that increases in the number of posts, comments, and reactions significantly predicted weight loss (β=–.94, P=.04); receiving comments positively predicted changes in self-efficacy (β=7.81, P=.009), and the degree to which one’s network neighbors are tightly connected with each other weakly predicted changes in perceived social support (β=7.70, P=.08). In addition, change in self-efficacy mediated the relationship between receiving comments and weight loss (β=–.89, P=.02). Conclusions Our analyses using data from this pilot study linked participants’ network characteristics with changes in several important study outcomes of interest such as self-efficacy, social support, and weight. Our results point to the potential of using social network analysis to understand the social processes and mechanisms through which web-based behavioral interventions affect participants’ psychological and behavioral outcomes. Future studies are warranted to validate our results and to further explore the relationship between network dynamics and study outcomes in similar and larger trials.

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The emerging viewertariat in South Korea: The Seoul mayoral TV debate on Twitter, Facebook, and blogs

Cited by 15 publications

References 37 publications

Mapping the political landscape of Persian Twitter: The case of 2013 presidential election

Mapping the political landscape of Persian Twitter: The case of 2013 presidential election

Measuring international relations in social media conversations

Social Network Analysis of the Effects of a Social Media–Based Weight Loss Intervention Targeting Adults of Low Socioeconomic Status: Single-Arm Intervention Trial

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