As the number and the diversity of news outlets on the Web grow, so does the opportunity for "alternative" sources of information to emerge. Using large social networks like Twitter and Facebook, misleading, false, or agenda-driven information can quickly and seamlessly spread online, deceiving people or influencing their opinions. Also, the increased engagement of tightly knit communities, such as Reddit and 4chan, further compounds the problem, as their users initiate and propagate alternative information, not only within their own communities, but also to different ones as well as various social media. In fact, these platforms have become an important piece of the modern information ecosystem, which, thus far, has not been studied as a whole. In this paper, we begin to fill this gap by studying mainstream and alternative news shared on Twitter, Reddit, and 4chan. By analyzing millions of posts around several axes, we measure how mainstream and alternative news flows between these platforms. Our results indicate that alt-right communities within 4chan and Reddit can have a surprising level of influence on Twitter, providing evidence that "fringe" communities often succeed in spreading alternative news to mainstream social networks and the greater Web.
Situngkir @cite_8 empirically studies an Indonesian hoax on Twitter, finding that it spread broadly and quickly (within two hours), and that it would have spread more if a conventional media outlet did not publicly deny it. He also argues that hoaxes can propagate easily if there is collaboration between the recipients of the hoax. @cite_9 present a case study based on a hostage crisis in Sydney, analyzing 5.4M tweets from three main perspectives: 1) volume (i.e., number of rumor-related messages per time interval), 2) exposure (i.e., number of individuals exposed to the rumor), and 3) content production (i.e., whether the content is written by the user or is re-shared). @cite_12 study two crisis-related incidents on Twitter aiming to determine the effect of official'' accounts with respect to the containment of rumors. Authors show that official account can significantly contribute to stopping the propagation of the rumor by actively engaging in conversations related to the incidents. Finally, @cite_2 study the dissemination of false rumors vs. confirmed news on Twitter the days following the 2010 earthquake in Chile, concluding that an aggregate analysis on the flow of tweets can distinguish the former from the latter.
@cite_9 @cite_2 @cite_12 @cite_8
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In this article we explore the behavior of Twitter users under an emergency situation. In particular, we analyze the activity related to the 2010 earthquake in Chile and characterize Twitter in the hours and days following this disaster. Furthermore, we perform a preliminary study of certain social phenomenons, such as the dissemination of false rumors and confirmed news. We analyze how this information propagated through the Twitter network, with the purpose of assessing the reliability of Twitter as an information source under extreme circumstances. Our analysis shows that the propagation of tweets that correspond to rumors differs from tweets that spread news because rumors tend to be questioned more than news by the Twitter community. This result shows that it is posible to detect rumors by using aggregate analysis on tweets. We discuss the way of hoax spreading as gossip and rumor throughout the social media, i.e.: Twitter, by observing an empirical case in Indonesia. We discuss the spreading factor of the gossip in the social media and see the epidemiology of the propagation hoax before and after the hoax being clarified in the conventional mass media. The discussions brought us to the open enrchiment analysis of the sociology of gossip and rumors within the online services like Twitter for future observation of human behavior. Following the 12 May 2008 Wenchuan, China, earthquake, discussion circulated on the Internet describing how the U.S. Geological Survey's earthquake notification lagged behind firsthand accounts sent through Twitter, a popular Internet-based service for sending and receiving short text messages, referred to as “tweets.” A prominent technology blogger, Robert Scoble (http: scobleizer.com), is generally credited for being the first to aggregate and redistribute tweets from people in China who directly experienced and reported the shaking resulting from the Wenchuan earthquake. @PARASPLIT Subsequent earthquakes generated volumes of earthquake-related tweets, and numerous accounts are on the Web. For example, Ian O'Neill discusses Twitter activity following a magnitude 3.3 Los Angeles earthquake on 24 January 2009 in his blog http: astroengine.com. He showed a remarkable increase in frequency of tweets containing the word “earthquake” after the event and discussed the possibility of a Twitter-based earthquake detector. Similarly, following the 30 March 2009, Morgan Hill, California, magnitude 4.3 earthquake, Michal Migursk (http: mike.teczno.com) noted an increase in earthquake-related tweets. @PARASPLIT Access to firsthand accounts of earthquake shaking within seconds of an earthquake is intriguing, but is there any reliable information that can be gleaned from the Twitter messages? To explore this question, we provide a quick review of Twitter and its capabilities and investigate the possibility of using the tweets to detect seismic events and produce rapid maps of the felt area. In this exploratory study, we examine the tweets that followed the 30 March 2009 Morgan Hill earthquake. @PARASPLIT Twitter is a service that allows anyone to send and receive 140-character text messages (tweets) via any Internet-enabled device. Tweets can be sent and received through a Web page, mobile device, or third-party Twitter applications. Tweets can be sent publicly or privately to a specified user. All users who opt to “follow” a Twitter user will receive that user's tweets … In this paper we highlight three distinct approaches to studying rumor dynamicsâ volume, exposure, and content production. Expanding upon prior work, which has focused on rumor volume, we argue that considering the size of the exposed population is a vital component of understanding rumoring. Additionally, by combining all three approaches we discover subtle features of rumoring behavior that would have been missed by applying each approach in isolation. Using a case study of rumoring on Twitter during a hostage crisis in Sydney, Australia, we apply a mixed-methods framework to explore rumoring and its consequences through these three lenses, focusing on the added dimension of exposure in particular. Our approach demonstrates the importance of considering both rumor content and the people engaging with rumor content to arrive at a more holistic understanding of communication dynamics. These results have implications for emergency responders and official use of social media during crisis management.