27,729 research outputs found

    Online Misinformation: Challenges and Future Directions

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    Misinformation has become a common part of our digital media environments and it is compromising the ability of our societies to form informed opinions. It generates misperceptions, which have affected the decision making processes in many domains, including economy, health, environment, and elections, among others. Misinformation and its generation, propagation, impact, and management is being studied through a variety of lenses (computer science, social science, journalism, psychology, etc.) since it widely affects multiple aspects of society. In this paper we analyse the phenomenon of misinformation from a technological point of view.We study the current socio-technical advancements towards addressing the problem, identify some of the key limitations of current technologies, and propose some ideas to target such limitations. The goal of this position paper is to reflect on the current state of the art and to stimulate discussions on the future design and development of algorithms, methodologies, and applications

    Fully Automated Fact Checking Using External Sources

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    Given the constantly growing proliferation of false claims online in recent years, there has been also a growing research interest in automatically distinguishing false rumors from factually true claims. Here, we propose a general-purpose framework for fully-automatic fact checking using external sources, tapping the potential of the entire Web as a knowledge source to confirm or reject a claim. Our framework uses a deep neural network with LSTM text encoding to combine semantic kernels with task-specific embeddings that encode a claim together with pieces of potentially-relevant text fragments from the Web, taking the source reliability into account. The evaluation results show good performance on two different tasks and datasets: (i) rumor detection and (ii) fact checking of the answers to a question in community question answering forums.Comment: RANLP-201

    Echoes of Populism and Terrorism in Libya’s Online News Reporting

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    This article focuses on news reporting in Libya, assessing both official and citizen journalism. Special attention is paid to online resources, primarily spontaneous posts written in Arabic. Social media shows the emergence of citizen journalism together with so-called User-generated Content. Both have proved capable of creating legitimacy. Political inclinations, including Islamic ideology and its religious claims, are presented, supported, or criticized by ordinary citizens who post their comments and opinions on the web. Official press and news agencies have their social media profiles as well, sharing the same online space with nonprofessionals. Monitoring and analysis of reporting show that there is no relevant difference in journalistic models; nor do concerns between professionals and nonprofessionals vary. Libya appears today to be a mosaic of different interests: one that is interconnected and in conflict at the same time. These interests are vying to establish new supremacies in the country. Journalism in its various typologies faces pressure from the abovementioned interests, so it is negatively affected by rhetoric in both reporting and commentary. These preliminary arguments lead us to the core topics of populism – for which a definition is suggested – and reporting about terrorism in Libya. Against this background, we analyze news flows, sources, and other issues. I conclude with a brief review of the main issues, the characteristics of the Arabic narrative discourse, and the emerging Arabic lexico

    $1.00 per RT #BostonMarathon #PrayForBoston: analyzing fake content on Twitter

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    This study found that 29% of the most viral content on Twitter during the Boston bombing crisis were rumors and fake content.AbstractOnline social media has emerged as one of the prominent channels for dissemination of information during real world events. Malicious content is posted online during events, which can result in damage, chaos and monetary losses in the real world. We analyzed one such media i.e. Twitter, for content generated during the event of Boston Marathon Blasts, that occurred on April, 15th, 2013. A lot of fake content and malicious profiles originated on Twitter network during this event. The aim of this work is to perform in-depth characterization of what factors influenced in malicious content and profiles becoming viral. Our results showed that 29% of the most viral content on Twitter, during the Boston crisis were rumors and fake content; while 51% was generic opinions and comments; and rest was true information. We found that large number of users with high social reputation and verified accounts were responsible for spreading the fake content. Next, we used regression prediction model, to verify that, overall impact of all users who propagate the fake content at a given time, can be used to estimate the growth of that content in future. Many malicious accounts were created on Twitter during the Boston event, that were later suspended by Twitter. We identified over six thousand such user profiles, we observed that the creation of such profiles surged considerably right after the blasts occurred. We identified closed community structure and star formation in the interaction network of these suspended profiles amongst themselves

    Social Media Influence: Metrics Matter

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    It is imperative for companies to engage in social media marketing as consumers are often dependent on online information and electronic word-of-mouth. Past literature claims that consumers evaluate the influence of communications differently on social media than they would in a traditional environment because of the nature of the internet. This study aims to analyze user’s perceptions of social media marketing influence and determines if user’s perception of influence changes based on the number of social media metrics (likes, comments, and shares) that accompany a Facebook post. The study also investigates if perceptions of influence vary depending on a user’s level of involvement in the situation. A 2x2 factorial design is utilized to manipulate both level of involvement and amount of likes, comments, and shares that accompany a Facebook post. The results contend that a high number of likes, comments, and shares on Facebook leads to increased perceptions of source credibility and information usefulness. In particular, the results prove that a high number of likes, comments, and shares on Facebook leads to increased purchase intention in a low-involvement situation. These results are essential to marketers as they prove the importance of curating engaging content on company’s Facebook pages in order to generate high amounts of likes, comments, and shares. Increasing the amount of likes, comments, and shares on Facebook will make the post more influential to users
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