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Antagonistic bias: developing a typology of agonistic talk on Twitter using gun control networks

机译:敌对偏见:使用枪控制网络开发Twitter上的激动谈话的类型

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Purpose The purpose of this paper is to apply Connolly's (2003) concept of agonistic respect to develop a typology of agonistic/antagonistic discourses on Twitter. To develop the typology, this study examines 2,236 Tweets containing the hashtag #guncontrol and uses NodeXL (Smith et al., 2010) to create a network map from which the 75 most influential accounts are derived . Using constant-comparative analysis (Glaser and Strauss, 1967), the authors identify seven categories of discourse style based on Connoly's (2001) notion of ressentiment and "good faith presentations" of opposing arguments: furtive/secretive, cravenly opportunistic, willfully ignorant, irrational sentimental, misunderstanding/misguided, contingently wrong and reciprocal inquiry. The typology provides a useful and unique way to operationalize agonistic democratic theory and serves as the possible basis for training a machine learning classifier to detect antagonistic discourses on social media platforms. Design/methodology/approach To determine the level of agonism on Twitter, the authors examine tweets that employed the hashtag #guncontrol on March 12, 2018, one month after the shooting at the Marjory Stoneman Douglass High School in Parkland, Florida on February 14. The authors used the NodeXL excel add-on to collect and map 2,236 tweets. Using grounded theory/constant-comparative analysis (Glaser and Strauss, 1967), the authors develop a typology of seven types of discourses ordered from most antagonistic to most agonistic using Connolly's (1993) concept of agonistic respect. Findings After examining the top 75 most shared tweets and using constant-comparative analysis to look for patterns of similarity and dissimilarity, the authors identified seven different ways in which individuals present their opponents' value positions on Twitter on the issue of gun control. The authors were guided by agonistic theory in the authors' inquiry. The authors looked at how Twitter users expressed their opponent's faith/value positions, how pluralistic the discourse space was in the comment threads and how much the "talk" was likely to elicit ressentiment from adversaries. Research limitations/implications - Because the authors intended to engage in theory building, the authors limited the analysis to a selected number of tweets on one particularly salient topic, on one day. The intent of this was to allow for a close reading of the tweets in that specific network for the purposes of creating a useful typology that can be applied to a broader range of cases/issues/platforms. Practical implications - The authors hope that typology could serve as a potential starting point for Twitter to think about how it could design its algorithms toward agonistic talk. The typology could be used as a classification scheme to differentiate agonistic from antagonistic threads. An algorithm could be trained to spot threads overwhelmingly populated by antagonistic discourse and instructed to insert posts from other threads that represent agonistic responses like "contingently wrong" or "reciprocal inquiry." While generous presentations or deeper, more nuanced presentations of the opponent's value position are not a panacea, they could serve to change the orientation by which users engage with policy issues. Social implications - Social media platforms like Twitter have up to now been left alone to make markets and establish profitability off of public sphere conversations.The result has been a lack of attention to how discourse on these platforms affects users mental well-being, community health and democratic viability. Recently, Twitter's CEO has indicated a need to rethink the ways in which it promotes "healthy discourse." The utilitarian presumption that, left to our own devices, we will trial and error our way to the collective good does not account for the importance of others in refining one's preferences, arguments and world views. Without an "other" to vet ideas and lead us toward becoming wiser, we are left with a Wyly antagonism that moves discourse further and further away from agonistic respect and toward antagonistic virtual struggle. Platforms that allow antagonistic talk that breeds ressentiment run the risk of irrevocably damaging democracy through poisoning its public sphere. Originality/value This paper is unique in providing a typology/framework for thinking about the types of "political talk" that exists on Twitter. By using agonistic political theory as a framework, the authors are able to establish some guiding principles for "good political talk" that acknowledges the incommensurability of value positions on issues like gun control. The typology's emphasis on agonistic respect, ressentiment and generosity in the presentation of alternative value positions provides a starting point from which to map and catalog discourse on Twitter more generally and offers a normative model for changing algorithmic design.
机译:目的本文的目的是应用康诺利斯(2003)激动的概念,以开发Twitter上的激动/拮抗散文的类型。为了开发类型化,该研究检查了包含HashTag #gunControl的2,236推文,并使用Nodexl(Smith等,2010)来创建从中派生75个最有影响力的帐户的网络地图。使用常量比较分析(Glaser和Strauss,1967),作者识别基于Connoly(2001)的喧嚣和“诚信介绍”的七类话语风格,相反论点:偷偷摸摸/秘密,蠕动的机会主义,故意无知,非理性的感情,误解/误导,常见的错误和互惠询问。类型学提供了一种有用而独特的方式来运作激动主义民主理论,并作为培训机器学习分类器的可能依据,以检测社交媒体平台上的对抗致密。作者审查了2018年3月12日在2018年3月12日在佛罗里达州佛罗里达州佛罗里达州佛罗里达州佛罗里达州佛罗里达州的射击之后雇用Hashtag #GunControl的推文。作者使用了Nodexl Excel加载项来收集和地图2,236推文。使用接地理论/常量比较分析(Glaser和Strauss,1967),作者开发了一种从最拮抗大多数激动论的七种类型的散文,使用Connolly(1993)的激动尊重的概念。调查结果在检查前75个最多分享的推文和使用常量比较分析寻找相似性和不相似的模式,确定了七种不同的方式,其中个人在枪支控制问题上向Twitter展示其对手的价值职位。作者在作者询问中被激动理论所指导。作者看着Twitter用户如何表达他们的对手的信仰/价值职位,话语空间在评论线程中是多么多元化,以及“谈话”可能会引起来自对手的喧嚣。研究限制/含义 - 因为作者旨在从事理论建设,作者将分析限制在一天特别突出的话题上的选定数量的推文。其中的意图是为了允许在该特定网络中仔细阅读推文,以创建有用的类型,这些类型可以应用于更广泛的案例/问题/平台。实际意义 - 作者希望类型学能够成为推特考虑如何将其算法设计到激动谈话的算法的潜在起点。类型学可以用作分类方案,以区分来自拮抗线程的激动。可以训练一种算法,以训练以敌对话语的占据压倒性地填充的挑战,并指示从其他线程插入帖子,这些帖子代表像“常见错误”或“互惠查询一样”。虽然慷慨的演示或更深的演示,对手的价值位置的更细微的介绍不是一个灵丹妙药,但它们可以用于改变用户与政策问题互动的方向。社会影响 - 像Twitter这样的社交媒体平台现在已经独自留下了市场,并建立了公共球体对话的盈利能力。结果一直缺乏对这些平台的话语如何影响用户心理健康的话语和民主的可行性。最近,Twitter的首席执行官表示需要重新思考其促进“健康话语”的方式。功利主义推定认为,我们将留给我们自己的设备,我们将审判和错误我们对集体好的方式,不会占他人在炼制一个人的偏好,论点和世界观点方面的重要性。如果没有“其他”兽医的想法并导致我们变得更加愿意,我们留下了一个令人害怕的对抗,进一步举动话语,远离激动主义尊重和对抗敌人的虚拟斗争。允许敌对谈论的平台通过中毒,培育桶的敌人谈判冒着不可逆转地破坏民主的风险。原创性/值本文在提供了思考Twitter上存在的“政治谈话”类型的类型学/框架时是独一无二的。通过使用激动的政治理论作为框架,作者能够为“良好的政治谈话”建立一些指导原则,以确认枪支控制等问题的价值职位不堪责任。替代价值位置呈现中,Tepology对激动主义尊重,鲁森特和慷慨提供了一种从中映射和目录话语更普遍的起点,并提供了改变算法设计的规范模型。

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