Literature DB >> 29182493

Japan's 2014 General Election: Political Bots, Right-Wing Internet Activism, and Prime Minister Shinzō Abe's Hidden Nationalist Agenda.

Fabian Schäfer1, Stefan Evert1, Philipp Heinrich1.   

Abstract

In this article, we present results on the identification and behavioral analysis of social bots in a sample of 542,584 Tweets, collected before and after Japan's 2014 general election. Typical forms of bot activity include massive Retweeting and repeated posting of (nearly) the same message, sometimes used in combination. We focus on the second method and present (1) a case study on several patterns of bot activity, (2) methodological considerations on the automatic identification of such patterns and the prerequisite near-duplicate detection, and (3) we give qualitative insights into the purposes behind the usage of social/political bots. We argue that it was in the latency of the semi-public sphere of social media-and not in the visible or manifest public sphere (official campaign platform, mass media)-where Shinzō Abe's hidden nationalist agenda interlocked and overlapped with the one propagated by organizations such as Nippon Kaigi and Internet right-wingers (netto uyo) during the election campaign, the latter potentially forming an enormous online support army of Abe's agenda.

Entities:  

Keywords:  Japan's 2014 general election; Twitter; computational propaganda; internet right-wingers; near-duplicate detection; populism; social bots

Mesh:

Year:  2017        PMID: 29182493      PMCID: PMC5733662          DOI: 10.1089/big.2017.0049

Source DB:  PubMed          Journal:  Big Data        ISSN: 2167-6461            Impact factor:   2.128


  2 in total

1.  A Confirmation Bias View on Social Media Induced Polarisation During Covid-19.

Authors:  Sachin Modgil; Rohit Kumar Singh; Shivam Gupta; Denis Dennehy
Journal:  Inf Syst Front       Date:  2021-11-20       Impact factor: 5.261

2.  Japanese conservative messages propagate to moderate users better than their liberal counterparts on Twitter.

Authors:  Mitsuo Yoshida; Takeshi Sakaki; Tetsuro Kobayashi; Fujio Toriumi
Journal:  Sci Rep       Date:  2021-10-04       Impact factor: 4.379

  2 in total

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