Taking stock of social-political polarization in Asia: political communication, social media and digital governance

Abstract

During the 2016 American presidential election, the possible impact of social media algorithm and echo chamber effects on socio-political polarization and perhaps even voting results, attracted much scholarly attention. Such socio-political polarization was present, at least to a degree, also in Asian countries with diverse political and cultural systems. Exposure to heterogeneous perspectives has been found to enhance individuals’ political participation when they get used to diverse online discourse environments (Kim, Hsu, & de Zúñiga, 2013). In contrast, those in information cocoons surrounded by similar viewpoints or like-minded values, tended to filter out dissenting views, firm in their specific world views, and tended to go to extremes easily (Sunstein, 2009). Two opposing arguments about the Internet and social media depict different attributes of polarization. On one hand, the openness of the Internet allows individuals to receive different ideas, which likely decreases the effects of polarization (Garrett, Carnahan, & Lynch, 2013; Hong & Kim, 2016). On the other hand, as increasing empirical evidence shows, polarization can be exacerbated under selective exposure to divisive ideologies and information on social network sites. Social media is considered a contributor to ideology polarization as its algorithm leads to filter bubbles that screen out differing views while enhancing similar political beliefs and perspectives (Hong & Kim, 2016). Through algorithmic personalization, liked-minded contents are promoted or filtered, which magnifies the effects of the echo chamber (Dubois & Blank, 2018). Evidence of echo chambers on social media is supported by studies using digital trace data (Terren & Borge, 2021). Social media heavy users are likely to have scanty network heterogeneity as a result of limited exposure to different perspectives, which reinforces polarization as a result of less exposure to diverse viewpoints (Lee, Choi, Kim, & Kim, 2014). Internet and social media algorithms have been criticized for worsening social-political polarization when these black-box machinery mechanisms predetermine users’ exposure to information. Those exposed to homogeneous political views believe their views are held by the majority, which deepens the gulf between political parties or social groups different from them and thus cause political turmoil and societal chaos. Yarchi, Baden, and Kligler-Vilenchik’s (2020) computational communication research confirms social media effects on political polarization. According to Yarchi et al. (2020), political polarization are categorized into interactional polarization, positional polarization and affective polarization. Political polarization is shaped by individual political attitudes or partisan dispositions (Coffey & Joseph, 2012). Media framing, as the second-level of agenda setting, selects and emphasizes facts and interpretations to shape public perceptions and tell stories to conform to their media narratives (Morstatter, Wu, Yavanoglu, Corman, & Liu, 2018). The partisan framing of conflicts is shown in mass media. Attention to political news influences viewer behaviors and aggravates polarization, which is strongly affected by individual partisan and ideological dispositions (Coffey & Joseph, 2012). Through algorithmic customization, social media use that involves complexity of multi-stakeholders’ agenda-setting and framing forces is regarded as effective tools to