In online debates, as in offline ones, individual utterances or arguments support or attack each other, leading to some subset of arguments winning (potentially from different sides of the debate). However, online conversations are much larger in scale than offline ones, with often hundreds of thousands of users weighing in, and so, readers are often forced to sample a subset of the arguments or arguments being put forth. Since such sampling is rarely done in a principled manner, users may not get all the relevant "winning" arguments to get a full picture of the debate from a sample. This paper is interested in answering the question of how users should sample online conversations to selectively favour winning arguments. We apply techniques from argumentation theory and complex networks to build a model that predicts the probabilities of the normatively winning arguments given their location in idealised online discussions. Online discussions are modeled as reply networks where nodes represent the comments exchanged and directed edges represent replies that can either be supporting or attacking. Our model shows that the proportion of replies that are supporting in the network, the network's in-degree distribution and the locations of unrebutted arguments ("the last words") all determine the behaviour of the probability that a comment is a winning argument given its location. This is also verified with data scraped from the online debating platform Kialo. In predicting the locations of the winning arguments in reply networks, we can therefore suggest which arguments a reader should sample and read if he or she would like to grasp the winning opinions in such discussions. Our models have important implications for the design of future online discussion platforms.
It is important to study online discussions because they can affect the offline world. For example, @cite_36 has shown that large companies (as defined by Forbes) may actively censor critical comments. However, the magnitude of such effects is open for debate in some cases. For example, @cite_32 has clarified the factors behind how much the spread of fake news on social media can be responsible for influencing the 2016 US Presidential Election from the perspective of welfare economics, and argued that there are good reasons to argue that the effects are both small and large. Also, Twitter allows for UK MPs to follow other MPs; which may facilitate cross-party discussions despite ideological differences @cite_39 . But on the individual level, we seek to understand how information can be presented to them such that they read the most compelling of comments made in a discussion.
@cite_36 @cite_32 @cite_39
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Purpose – Of Fortune 100 companies 79 percent use some form of social media to communicate with customers and other stakeholders. However, these media pose the risk of providing a forum for comments critical of corporate leadership, services, or products. Most marketing specialists recommend that negative comments should be treated as opportunities to resolve potential problems. This paper seeks to assess whether large companies adopt the recommended approach when reacting to negative comments.Design methodology approach – The study identifies official Facebook pages sponsored by the top ten companies (as defined by the Forbes 2000 for 2010) in four industry groups – banking, retailing, software and services, and household and personal products. The number of negative comments posted to these pages is calculated and corporate reactions to the comments analyzed.Findings – The study concludes that large corporations do not generally approach negative comments as public relations opportunities, but prefer to... Following the 2016 U.S. presidential election, many have expressed concern about the effects of false stories (“fake news”), circulated largely through social media. We discuss the economics of fake news and present new data on its consumption prior to the election. Drawing on web browsing data, archives of fact-checking websites, and results from a new online survey, we find: (i) social media was an important but not dominant source of election news, with 14 percent of Americans calling social media their “most important” source; (ii) of the known false news stories that appeared in the three months before the election, those favoring Trump were shared a total of 30 million times on Facebook, while those favoring Clinton were shared 8 million times; (iii) the average American adult saw on the order of one or perhaps several fake news stories in the months around the election, with just over half of those who recalled seeing them believing them; and (iv) people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks. Disengagement and disenchantment with the Parliamentary process is an important concern in today's Western democracies. Members of Parliament (MPs) in the UK are therefore seeking new ways to engage with citizens, including being on digital platforms such as Twitter. In recent years, nearly all (579 out of 650) MPs have created Twitter accounts, and have amassed huge followings comparable to a sizable fraction of the country's population. This paper seeks to shed light on this phenomenon by examining the volume and nature of the interaction between MPs and citizens. We find that although there is an information overload on MPs, attention on individual MPs is focused during small time windows when something topical may be happening relating to them. MPs manage their interaction strategically, replying selectively to UK-based citizens and thereby serving in their role as elected representatives, and using retweets to spread their party's message. Most promisingly, we find that Twitter opens up new avenues with substantial volumes of cross-party interaction, between MPs of one party and citizens who support (follow) MPs of other parties.