Distinguishing Fake News Online Abstract

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DistinguishingFake News Online

Abstract

Socialmedia platforms are overwhelmed by both official and misleading news. The websites have made it possible for anyone to create broadcastswithout any deterrence. Unfortunately, the great informationdemocracy leads to the publication of inaccurate reports. In somecases, the bogus broadcasts may originate from fortuitousmisinterpretation of messages. However, some people deliberatelydistort existing news to lead the public astray. Differencing betweenrumors and legitimate news is often hard to many people. Scientistshave developed various techniques to help readers and subscribers ofdifferent social websites to identify sham bulletins. Some of thesetechniques include the account-based features and data collectionapplications that are designed to identify rumors using givenkeywords (Chun, Liang, Xu, &amp Yang, 2016). The approaches can beapplied in the evaluation of diverse forms of news found in thesocial media such as blog posts, memes, and satirical broadcastoutlets. Their intention is to minimize the damage that may occur inthe offline environment due to the circulation of false information.

Keywords:fake news, misinformation, propaganda, account-based features, socialmedia platforms, broadcast outlets

DistinguishingFake News Online

Fakenews is a common concept used to spread propaganda. Different sourcespublish made up information to attract leaders in their websites andblogs. In other cases, the gossip is intended to entertain thereaders. The internet plays a crucial role in spreading news acrossthe world, but it makes it vulnerable to misinforming the targetgroup.

Thesisstatement. Fake news circulates on social media because the platformshave made it possible for anyone to publish individual broadcasts andthere lacks a proper oversight on nature disseminated reports.

DifferentTypes of Fake News and Misinformation on the Internet

Falsereports are produced in large quantities and their time of emergenceis close to the actual occurrence. According to Ciampaglia, Flammini,Menczer, and Shao (2016), the information tends to come up almostimmediately after a given incident takes place. Besides, it is widelyshared to reach a big audience. Authentic information, on thecontrary, has a delay of about thirteen hours, which facilitates factchecking.

Thesame study found that tweets spreading unsubstantiated bulletinssurpassed the ones containing accurate reports by far. It isnoteworthy that the false facts tend to originate from one source. Incase the story is published on other websites or printed dailies,they all give credit to one source. Validated reports originate frommultiple and independent publishers. Conducting a Google search is asuitable way to authenticate the legitimacy of news, as it wouldindicate whether popular media houses are also running the wholestory (Ciampaglia et al., 2016).

HowFake News is Spread Across Social Media

Thefalse news and misinformation spread across the social mediaplatforms come about in wide-ranging ways. Mei, Qazvinian, Radev, andRosengren (2011) state that memes are among the media used to spreadrumors on the social sites. Applications such as the “TruthySystem” track specific quotes replicated online to establishmisleading political mimics. Posting wrong messages that arecomplemented by false images is another common strategy used tospread propaganda. For instance, when a natural disaster happens,several people send updated news regarding the event, pray for thevictims, and express sympathy. Other users share the same messageseven when the pictures tagged, and communication made lacksauthenticity. For example, several users retweeted messages updatedby individuals during the Hurricane Sandy despite that most of themcontained inaccurate information such as the incorrect location ofthe events referred (Lee &amp Rajdev, 2015).

Blogsalso offer a platform for spreading the fake news online. Accordingto Chen, Conroy, and Rubin (2015), some media outlets deliberatelypublish false news on their blogs with the intention of manipulatingreaders to believe in a given concept. The action is different frompractical jokes since the reports look authentic. In some cases, thetraditional news bulletin outlets may endorse the broadcastsmisguidedly.

Somepeople are unable to make a distinction between official reports andmisinformation. Ciampaglia et al. (2016) assert that social mediahave facilitated everyone to create news. Microblogs such as Twitterallow users to rebroadcast messages updated by their followers. Onthe long run, there lacks a sole authority that can regulate theinformation shared online. The existence of platforms with no one tooversee the content circulated provides an egalitarian informationaccess model. However, the lack of oversight exposes readers to theinadvertent dissemination of inaccurate broadcasts (Ciampaglia etal., 2016).

ThreeDifferent Techniques that Researchers Are Proposing or Have DevelopedTo Help Social Media Sites Automatically Detect Fake News orMisinformation

Followingthe open publication of information on social media sites,researchers have developed cutting edge applications and evaluationmethods to distinguish between authentic and misinformation. Chun,Liang, Xu, and Yang (2016) use Sina Weibo microblog case study. Theorganization runs account-based features such as the @WeiboPiyaoaccount, which is maintained by experienced journalists and expertsfrom the Sina Corporation. They identify common rumors and cautiontheir followers against the stories.

Similarly,the website also operates secondary features for identifying fakenews like the WeiboMisinformation-Declarationplatform, which any subscriber can use to report unauthentic news tothe staff in charge of the account. The professionals then analyzethe highlighted cases before releasing their final decisions throughthe same account. Despite that it can take over 24 hours beforefeedback is available the service plays an essential role inprotecting Weibo subscribers against unsubstantiated broadcasts (Chunet al., 2016).

Lastly,a dataset construction can help to identify particular rumors. Theapproach utilizes given keywords that are attributed to the previousunconfirmed news. Twitter Monitor is an example of a datasetconstruction application used to track misinformation throughestablishing the number of tweets containing incorrect information.In the case of Weibo, the evaluation of keywords is conductedmanually (Chun et al., 2016).

Conclusion

Inconclusion, fake news is common on social media. Sometimes thereports originate from the deliberate effort of individuals lookingto spread propaganda. However, some false stories are meted out byunsuspecting web users. Misinformation spreads on online social mediaplatforms in various ways, including tweets, blog posts, andsatirical news outlets. In the recent past, scientists haveestablished diverse tactics such as dataset construction applicationsand account-based features to recognize rumors easily.

References

Chen,Y., Conroy, N.J., &amp Rubin, V.L. (2015). Deception detection fornews: Three types of fakes. Languageand information Research Lab.

Ciampaglia,G.L., Flammini, A., Menczer, F., &amp Shao, C. (2016). Hoaxy: Aplatform for tracking online misinformation. InternationalWorld Wide Web Conferences Steering Committee.Retrieved from http://dl.acm.org/citation.cfm?doid=2872518.2890098.

Lee,K. &amp Rajdev, M. (2015). Fake and spam messages: Detectingmisinformation during natural disasters on social media. 2015International Conference on Web Intelligence and Intelligent AgentTechnology,pp. 16 -20.

Liang,G., Xu, Chun., &amp Yang, J. (2016). Automatic rumor identificationon Sina Weibo. InternationalConference on Natural Computation, Fuzzy Systems and KnowledgeDiscovery (ICNC – FSKD),1523 -1531.

Mei,Q., Qazvinian, V., Radev, D.R., and Rosengren, E. (2011). Rumor hasit: Identifying misinformation in microblogs. Associationfor Computational Linguistics,pp. 1589 -1599.