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The spreading of misinformation online Open
Significance The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web is a fruitful environment for the mas…
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Validating the demographic, political, psychological, and experimental results obtained from a new source of online survey respondents Open
Researchers have increasingly turned to online convenience samples as sources of survey responses that are easy and inexpensive to collect. As reliance on these sources has grown, so too have concerns about the use of convenience samples i…
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Rumors and Health Care Reform: Experiments in Political Misinformation Open
This article explores belief in political rumors surrounding the health care reforms enacted by Congress in 2010. Refuting rumors with statements from unlikely sources can, under certain circumstances, increase the willingness of citizens …
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Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks Open
Social media has been developing rapidly in public due to its nature of spreading new information, which leads to rumors being circulated. Meanwhile, detecting rumors from such massive information in social media is becoming an arduous cha…
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Rumor Detection on Twitter with Tree-structured Recursive Neural Networks Open
Automatic rumor detection is technically very challenging. In this work, we try to learn discriminative features from tweets content by following their non-sequential propagation structure and generate more powerful representations for ide…
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Detect Rumors in Microblog Posts Using Propagation Structure via Kernel Learning Open
How fake news goes viral via social media? How does its propagation pattern differ from real stories? In this paper, we attempt to address the problem of identifying rumors, i.e., fake information, out of microblog posts based on their pro…
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An exploration of how fake news is taking over social media and putting public health at risk Open
Recent statistics show that almost 1/4 of a million people have died and four million people are affected either with mild or serious health problems caused by coronavirus (COVID‐19). These numbers are rapidly increasing (World Health Orga…
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Rumor Detection over Varying Time Windows Open
This study determines the major difference between rumors and non-rumors and explores rumor classification performance levels over varying time windows-from the first three days to nearly two months. A comprehensive set of user, structural…
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Tracing Fake-News Footprints Open
When a message, such as a piece of news, spreads in social networks, how can we classify it into categories of interests, such as genuine or fake news? Classification of social media content is a fundamental task for social media mining, a…
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A Survey on Information Diffusion in Online Social Networks: Models and Methods Open
By now, personal life has been invaded by online social networks (OSNs) everywhere. They intend to move more and more offline lives to online social networks. Therefore, online social networks can reflect the structure of offline human soc…
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CREDBANK: A Large-Scale Social Media Corpus With Associated Credibility Annotations Open
Social media has quickly risen to prominence as a news source, yet lingering doubts remain about its ability to spread rumor and misinformation. Systematically studying this phenomenon, however, has been difficult due to the need to collec…
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Communicating COVID-19 information on TikTok: a content analysis of TikTok videos from official accounts featured in the COVID-19 information hub Open
Amid the COVID-19 pandemic, TikTok, an emerging social media platform, has created an information hub to provide users with engaging and authoritative COVID-19 information. This study investigates the video format, type and content of the …
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Detect Rumors on Twitter by Promoting Information Campaigns with Generative Adversarial Learning Open
Rumors can cause devastating consequences to individual and/or society. Analysis shows that widespread of rumors typically results from deliberately promoted information campaigns which aim to shape collective opinions on the concerned new…
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Detect Rumor and Stance Jointly by Neural Multi-task Learning Open
In recent years, an unhealthy phenomenon characterized as the massive spread of fake news or unverified information (i.e., rumors) has become increasingly a daunting issue in human society. The rumors commonly originate from social media o…
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Interpretable Rumor Detection in Microblogs by Attending to User Interactions Open
We address rumor detection by learning to differentiate between the community's response to real and fake claims in microblogs. Existing state-of-the-art models are based on tree models that model conversational trees. However, in social m…
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A War of (Mis)Information: The Political Effects of Rumors and Rumor Rebuttals in an Authoritarian Country Open
Despite the prevalence of anti-government rumors in authoritarian countries, little is currently known about their effects on citizens’ attitudes toward the government, and whether the authorities can effectively combat rumors. With an exp…
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Social media in times of crisis: Learning from Hurricane Harvey for the coronavirus disease 2019 pandemic response Open
In recent times societal crises such as the coronavirus disease 2019 outbreak have given rise to a tension between formal ‘command and control’ and informal social media activated self-organising information and communication systems that …
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Rumor Detection by Exploiting User Credibility Information, Attention and Multi-task Learning Open
In this study, we propose a new multi-task learning approach for rumor detection and stance classification tasks. This neural network model has a shared layer and two task specific layers. We incorporate the user credibility information in…
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RETRACTED: COVID-19 as an “Infodemic” in Public Health: Critical Role of the Social Media Open
The Coronavirus disease 2019 (COVID-19) pandemic has emerged as a significant and global public health crisis. Besides the rising number of cases and fatalities, the outbreak has also affected economies, employment and policies alike. As b…
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Distress and rumor exposure on social media during a campus lockdown Open
Significance During active shooter events when danger is imminent and official information is disseminated inconsistently, ambiguity is high. In these situations, individuals may seek information from unofficial channels (e.g., social medi…
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Role of centrality for the identification of influential spreaders in complex networks Open
The identification of the most influential spreaders in networks is important to control and understand the spreading capabilities of the system as well as to ensure an efficient information diffusion such as in rumorlike dynamics. Recent …
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Defensive Modeling of Fake News Through Online Social Networks Open
Online social networks (OSNs) have become an integral mode of communication among people and even nonhuman scenarios can also be integrated into OSNs. The evergrowing rise in the popularity of OSNs can be attributed to the rapid growth of …
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Rumor Diffusion and Convergence during the 3.11 Earthquake: A Twitter Case Study Open
We focus on Internet rumors and present an empirical analysis and simulation results of their diffusion and convergence during emergencies. In particular, we study one rumor that appeared in the immediate aftermath of the Great East Japan …
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Rumor Detection on Social Media with Graph Structured Adversarial Learning Open
The wide spread of rumors on social media has caused tremendous effects in both the online and offline world. In addition to text information, recent detection methods began to exploit the graph structure in the propagation network. Howeve…
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Tree LSTMs with Convolution Units to Predict Stance and Rumor Veracity in Social Media Conversations Open
Learning from social-media conversations has gained significant attention recently because of its applications in areas like rumor detection. In this research, we propose a new way to represent social-media conversations as binarized const…
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The Genesis of the Birther Rumor: Partisanship, Racial Attitudes, and Political Knowledge Open
A growing body of work has examined the psychological underpinnings of conspiracy theory endorsement, arguing that the propensity to believe in conspiracy theories and political rumors is a function of underlying predispositions and motiva…
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IKM at SemEval-2017 Task 8: Convolutional Neural Networks for stance detection and rumor verification Open
This paper describes our approach for SemEval-2017 Task 8. We aim at detecting the stance of tweets and determining the veracity of the given rumor. We utilize a convolutional neural network for short text categorization using multiple fil…
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Towards Propagation Uncertainty: Edge-enhanced Bayesian Graph Convolutional Networks for Rumor Detection Open
Lingwei Wei, Dou Hu, Wei Zhou, Zhaojuan Yue, Songlin Hu. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Pap…
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Fully Automated Fact Checking Using External Sources Open
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 …
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Multiple Rumor Source Detection with Graph Convolutional Networks Open
Detecting rumor source in social networks is one of the key issues for defeating rumors automatically. Although many efforts have been devoted to defeating online rumors, most of them are proposed based an assumption that the underlying pr…