本文运用数据挖掘与分析方法，以Twitter上中国议题的分布与互动为分析对象，解 析社交机器人的舆论操纵行为，探究其行为模式及其与人类的交互关系。在抓取358,656 条推文、测量用户的机器人评分后发现，与中国相关的推文中有超过1/5疑似由机器人 用户发布。不同议题的自动化操纵程度存在差异。在用户互动网络中，机器人用户转 发、提及，但较少引用或回复。机器人可以成功地引发人类用户主动与之互动, 但人类 更倾向于与人类交互。研究认为，在传播内容上，社交机器人的存在可增加人类用户对 于特定信息的接触；在用户交互层面，社交机器人可以成功渗入社交网络，改变既有的 信息交互结构。

To understand how Twitter bots and trolls ("bots") promote online health content.We compared bots' to average users' rates of vaccine-relevant messages, which we collected online from July 2014 through September 2017. We estimated the likelihood that users were bots, comparing proportions of polarized and antivaccine tweets across user types. We conducted a content analysis of a Twitter hashtag associated with Russian troll activity.Compared with average users, Russian trolls (χ(1) = 102.0; P < .001), sophisticated bots (χ(1) = 28.6; P < .001), and "content polluters" (χ(1) = 7.0; P < .001) tweeted about vaccination at higher rates. Whereas content polluters posted more antivaccine content (χ(1) = 11.18; P < .001), Russian trolls amplified both sides. Unidentifiable accounts were more polarized (χ(1) = 12.1; P < .001) and antivaccine (χ(1) = 35.9; P < .001). Analysis of the Russian troll hashtag showed that its messages were more political and divisive.Whereas bots that spread malware and unsolicited content disseminated antivaccine messages, Russian trolls promoted discord. Accounts masquerading as legitimate users create false equivalency, eroding public consensus on vaccination. Public Health Implications. Directly confronting vaccine skeptics enables bots to legitimize the vaccine debate. More research is needed to determine how best to combat bot-driven content.

Social bots, or algorithmic agents that amplify certain viewpoints and interact with selected actors on social media, may influence online discussion, news attention, or even public opinion through coordinated action. Previous research has documented the presence of bot activities and developed detection algorithms. Yet, how social bots influence attention dynamics of the hybrid media system remains understudied. Leveraging a large collection of both tweets (N = 1,657,551) and news stories (N = 50,356) about the early COVID-19 pandemic, we employed bot detection techniques, structural topic modeling, and time series analysis to characterize the temporal associations between the topics Twitter bots tend to amplify and subsequent news coverage across the partisan spectrum. We found that bots represented 8.98% of total accounts, selectively promoted certain topics and predicted coverage aligned with partisan narratives. Our macro-level longitudinal description highlights the role of bots as algorithmic communicators and invites future research to explain micro-level causal mechanisms.

This study tries to negotiate two competing hypotheses involving the obtrusiveness of issues in media agenda-setting study: the ‘obtrusive contingency’ and the ‘cognitive priming’ hypotheses. The former holds that an individual’s direct experience overwhelms the influence of media coverage, so agenda-setting effects decrease as the obtrusiveness of personal experience with an issue increases. On the other hand, the latter contends that personal experience with an issue enhances, rather than lessens agenda-setting effects. Based on a theory of associative network, the study argues that obtrusive issues show agenda-setting effects within a shorter time period as compared to unobtrusive ones. The degree to which the US is involved in foreign policy issues was considered a criterion to determine the obtrusiveness of the issues.

The agenda-setting hypothesis asserts that the media have an effect indirectly by choosing certain issues for emphasis, thus making those issues more salient to the audiences. The hypothesis, stated in such general terms, presents formidable conceptual and methodological difficulties that are dealt with in this article. A controlled study of the audiences of two newspapers with differing content emphases was conducted during the 1972 presidential campaign. The results show only moderate support for the agenda-setting hypothesis; the honesty in government issues, given heavy play in one of the two newspapers, failed to generate much enthusiasm among readers of either paper. In addition the results suggest agenda setting is not a broad and unqualified media effect. Predicted differences mainly were restricted to the less involved and less motivated partisans who were heavily dependent on the newspapers for their political news. Finally, the importance of studying issue saliences apart from political attitudes was illustrated by the relatively strong relationship between such saliences and voter turnout and direction.

This study examined the agenda-setting process and the role it may play on the Internet, specifically in electronic bulletin boards (EBB). Online media coverage of four issues from five news media were downloaded during the 1996 fall political campaign. The frequency of EBB discussions of each issue served as the surrogate for the public agenda. An ARIMA model cross-correlational test showed EBB discussions of three issues—immigration, health care, and taxes—correlated with news media coverage, with time lags varying from 1 day to 7 days. Only for abortion did the media have no apparent agenda-setting effect. Media coverage apparently can provide individuals with information they can use in their EBB specific-issue discussions.

This study examines the agenda-setting power of fake news and fact-checkers who fight them through a computational look at the online mediascape from 2014 to 2016. Although our study confirms that content from fake news websites is increasing, these sites do not exert excessive power. Instead, fake news has an intricately entwined relationship with online partisan media, both responding and setting its issue agenda. In 2016, partisan media appeared to be especially susceptible to the agendas of fake news, perhaps due to the election. Emerging news media are also responsive to the agendas of fake news, but to a lesser degree. Fake news coverage itself is diverging and becoming more autonomous topically. While fact-checkers are autonomous in their selection of issues to cover, they were not influential in determining the agenda of news media overall, and their influence appears to be declining, illustrating the difficulties fact-checkers face in disseminating their corrections.

This article analyzes intermedia agenda-setting processes during a national election campaign of 38 newspapers, online news sites, TV news programs, as well as a wire service, through semi-automatic content analysis and time series analysis. The theoretical assumption was that intermedia agenda-setting is determined by the production structures of certain media types, the opinion-leader role of specific media outlets, and issue-specific characteristics. The findings suggest that, despite previous evidence to the contrary, intermedia agenda-setting also occurs during election campaigns, with a short time lag of 1 day. Additionally, a medium’s opinion-leader role depends strongly on issue-specific characteristics, such as obtrusiveness and proximity, mediating the intermedia agenda-setting process. And the traditional role of print media as intermedia agenda-setters is found to be challenged by online news sites.

We investigate how the online news and Twitter framed the discussion about genetically modified mosquitoes, and the interplay between the two media platforms. The study is grounded in the theoretical frameworks of intermedia agenda setting, framing, and the issue-attention cycle and combines methods of manual and computational content analysis, and time series analysis. The findings show that the Twitter discussion was more benefit-oriented, while the news coverage was more balanced. Initially, Twitter played a leading role in framing the discussion about genetically modified mosquitoes. When the public learned about the issue, online news gained momentum and led the Twitter publics to discuss the risks of genetically modified mosquitoes. Based on the findings, we argue that the intermedia frame setting may change its direction over time, and different media outlets may be influential in leading different aspects of the conversation.

An infodemic is an emerging phenomenon caused by an overabundance of information online. This proliferation of information makes it difficult for the public to distinguish trustworthy news and credible information from untrustworthy sites and non-credible sources. The perils of an infodemic debuted with the outbreak of the COVID-19 pandemic and bots (i.e., automated accounts controlled by a set of algorithms) that are suspected of spreading the infodemic. Although previous research has revealed that bots played a central role in spreading misinformation during major political events, how bots behavior during the infodemic is unclear. In this paper, we examined the roles of bots in the case of the COVID-19 infodemic and the diffusion of non-credible information such as “5G” and “Bill Gates” conspiracy theories and content related to “Trump” and “WHO” by analyzing retweet networks and retweeted items. We show the segregated topology of their retweet networks, which indicates that right-wing self-media accounts and conspiracy theorists may lead to this opinion cleavage, while malicious bots might favor amplification of the diffusion of non-credible information. Although the basic influence of information diffusion could be larger in human users than bots, the effects of bots are non-negligible under an infodemic situation.

This exploratory study matches a content analysis sample of Time magazine coverage of two “concrete” issues (drug abuse, energy) and two “abstract” issues (nuclear arms race, federal budget deficit) with Gallup Poll data over a lengthy period to find confirmation of the hypothesis: The media set the agenda with news about specific news events which readers/viewers can visualize, but the effect does not hold for news abstractions hard for readers/viewers to relate to. The study develops measures, tested independently in a separate, second study reported, to divide issues into either concrete or abstract categories. In agenda-setting terms, the study concludes, concreteness increases news media agenda-setting power; abstractness decreases agenda-setting power.

This paper has two objectives. First, it categorizes the Twitter handles tweeted flu related information based on the amount of replies and mentions within the Twitter network. The collected Twitter accounts are categorized as media, health related individuals, organizations, government, individuals with no background with media or medical field, in order to test the relationship between centrality measures of the accounts and their categories. The second objective is to examine the relationship between the importance of the Twitter accounts in the network, centrality measures, and specific characteristics of each account, including the number of tweets and followers as well as the number of accounts followed and liked.Using Twitter search network API, tweets with "flu" keyword were collected and tabulated. Network centralities were calculated with network analysis tool, NodeXL. The collected Twitters accounts were content analyzed and categorized by multiple coders.When the media or organizational Twitter accounts were present in the list of important Twitter accounts, they were highly effective disseminating flu-related information. Also, they were more likely to stay active one year after the data collection period compared to other influential individual accounts.Health campaigns are recommended to focus on recruiting influential Twitter accounts and encouraging them to retweet or mention in order to produce better results in disseminating information. Although some individual social media users were valuable assets in terms of spreading information about flu, media and organization handles were more reliable information distributors. Thus, health information practitioners are advised to design health campaigns better utilizing media and organizations rather than individuals to achieve consistent and efficient campaign outcomes.Published by Elsevier Ireland Ltd.

Classic agenda-setting studies implied a zero-sum process, in which issues compete for media and public attention. Recent time series analyses on single issues have disregarded this central assumption. Evidence from a variety of sources was cited to illustrate that agenda-setting is a zero-sum game, due to the limited carrying capacity of the public agenda. A mathematical model was proposed to incorporate the strengths of both the classic approach and the time series technique. The model was tested with data on three recent issues. Results reveal both mutual competition and one-way attraction among issues.