Understanding social viewing through discussion network and emotion: A focus on South Korean presidential debates

Lee, Ji-Young; Choi, Yun Jung

doi:10.1016/j.tele.2018.03.009

Cited by 9 publications

(4 citation statements)

References 27 publications

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“…The literature emphasizes the significance of political persuasion in fostering a more engaged and healthy democratic society, particularly during political campaigns (Lee and Choi, 2018). When citizens are receptive to changing their political attitudes, it promotes diverse perspectives and cultivates greater harmony.…”

Section: Political Democracymentioning

confidence: 99%

“…Digital social media, in particular, is well-recognized for its capability to enable individuals and groups to make their voices heard, as evidenced by its use to support social movements (Alshare et al ., 2022; Li et al ., 2022; Srivastava and Eachempati, 2021). However, it can also contribute to detrimental practices such as polarization and populism (Lee and Choi, 2018; Wang et al ., 2015), making it a two-sided tool for both constructive and destructive purposes. As a result, the debate surrounding social media’s potential benefits and threats to polarization remains highly contested and complex, with inconsistent and contradictory findings (Lu et al ., 2022).…”

Section: Introductionmentioning

confidence: 99%

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Diving into the divide: a systematic review of cognitive bias-based polarization on social media

Xing,

Zhang,

Storey

et al. 2024

JEIM

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PurposeThe global prevalence of social media and its potential to cause polarization are highly debated and impactful. The previous literature often assumes that the ideological bias of any media outlet remains static and exogenous to the polarization process. By studying polarization as a whole from an ecosystem approach, the authors aim to identify policies and strategies that can help mitigate the adverse effects of polarization and promote healthier online discourse.Design/methodology/approachTo investigate online polarization, the authors perform a systematic review and analysis of approximately 400 research articles to explore the connection between cognitive bias and polarization, examining both causal and correlational evidence. The authors extensively evaluate and integrate existing research related to the correlation between online polarization and crucial factors such as public engagement, selective exposure and political democracy. From doing so, the authors then develop a PolarSphere ecosystem that captures and illustrates the process of online polarization formation.FindingsThe authors' review uncovers a wide range of associations, including ideological cognition, bias, public participation, misinformation and miscommunication, political democracy, echo chambers and selective exposure, heterogeneity and trust. Although the impact of bias on social media polarization depends on specific environments and internal/external conditions, certain variables exhibit strong associations across multiple contexts. The authors use these observations as a basis from which to construct PolarSphere, an ecosystem of bias-based polarization on social media, to theorize the process of polarization formation.Originality/valueBased on the PolarSphere ecosystem, the authors argue that it is crucial for governments and civil societies to maintain vigilance and invest in further research to gain a deep comprehension of how cognitive bias affects online polarization, which could lead to ways to eliminate polarization.

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Section: Political Democracymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Diving into the divide: a systematic review of cognitive bias-based polarization on social media

Xing,

Zhang,

Storey

et al. 2024

JEIM

View full text Add to dashboard Cite

show abstract

“…Emotion is a type of psychological activity produced by individuals together with cognition and consciousness. Social media gives users opportunities to express their views on personal issues and provides its users with opportunities to build emotional bonds with others based on shared experiences or attitudes [ 49 ]. Such sharing is objective in nature and usually reflects the certain emotional state and emotion intensity of the individual [ 50 ].…”

Section: Introductionmentioning

confidence: 99%

Factors Affecting Social Media Users’ Emotions Regarding Food Safety Issues: Content Analysis of a Debate among Chinese Weibo Users on Genetically Modified Food Security

Xiong

2021

Healthcare

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Social media is gradually building an online information environment regarding health. This environment is filled with many types of users’ emotions regarding food safety, especially negative emotions that can easily cause panic or anger among the population. However, the mechanisms of how it affects users’ emotions have not been fully studied. Therefore, from the perspective of communication and social psychology, this study uses the content analysis method to analyze factors affecting social media users’ emotions regarding food safety issues. In total, 371 tweet samples of genetically modified food security in Sina Weibo (similar to Twitter) were encoded, measured, and analyzed. The major findings are as follows: (1) Tweet account type, tweet topic, and emotion object were all significantly related to emotion type. Tweet depth and objectivity were both positively affected by emotion type, and objectivity had a greater impact. (2) Account type, tweet topic, and emotion object were all significantly related to emotion intensity. When the depths were the same, emotion intensity became stronger with the decrease in objectivity. (3) Account type, tweet topic, emotion object, and emotion type were all significantly related to a user’s emotion communication capacity. Tweet depth, objectivity, and user’s emotion intensity were positively correlated with emotion communication capacity. Positive emotions had stronger communication capacities than negative ones, which is not consistent with previous studies. These findings help us to understand both theoretically and practically the changes and dissemination of user’s emotions in a food safety and health information environment.

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“…Studies on the relationship between individual emotions and attitudes are rarely mentioned while most researchers consider emotions are equivalent to attitudes. For example, Lee and Choi [ 4 ] explored the underlying mechanism of the effects of social viewing discussion networks on emotions in the context of the 2017 South Korean presidential debates.…”

Section: Introductionmentioning

confidence: 99%

Modeling Network Public Opinion Propagation with the Consideration of Individual Emotions

Jing

Chen

et al. 2020

IJERPH

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The occurrence of popular social events causes fluctuations and changes of public emotions, while the rapid development of online social platforms and networks has made individual interactions more intense and further escalated public emotions into public opinion. However, there is a lack of consideration of individual emotions in the current research on online public opinion. Based on this, this paper firstly expounds the quantitative representation of attitude and emotion, analyzes the formation and propagation process of online public opinion by combining individual’s expression willingness, individual’s expression ability, attitude perception value, attitude change probability and other factors, and constructs a network public opinion propagation model that takes individual emotion into consideration. Finally, the main factors affecting the formation and propagation of network public opinion are discussed through simulation experiments. The results demonstrate that: (1) fear is conducive to the formation of online public opinion, but the speed is relatively slow; sadness is not conducive to the formation, but once enough people participate in the exchange of views, the formation of online public opinion will be faster; (2) the influence of online public opinion on individual emotions expands with the increase of the number of individual interactions; (3) different network structures impact differently on the propagation of public opinion. Among them, BA (BA network is a scale-free network model proposed by Barabasi and Albert in order to explain the generation mechanism of power law, BA model has two characteristics: growth and priority connection mechanism) and ER (ER network is a network with random connectivity proposed by Erdös-Renyi) random networks can promote the propagation of online public opinion, which is prone to “one-sided” online public opinion. WS small-world networks (proposed by Watts and Strogatz. It is a kind of network with short average path length and high clustering coefficient) and fully-connected networks have an inhibitory effect on the spread of online public opinion, easily maintaining the multi-dimensional nature of online public opinion.

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Understanding social viewing through discussion network and emotion: A focus on South Korean presidential debates

Cited by 9 publications

References 27 publications

Diving into the divide: a systematic review of cognitive bias-based polarization on social media

Diving into the divide: a systematic review of cognitive bias-based polarization on social media

Factors Affecting Social Media Users’ Emotions Regarding Food Safety Issues: Content Analysis of a Debate among Chinese Weibo Users on Genetically Modified Food Security

Modeling Network Public Opinion Propagation with the Consideration of Individual Emotions

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