Deception Detection Methods for News Discourse Victoria L

Deception Detection Methods for News Discourse Victoria L

Western University From the SelectedWorks of Victoria Rubin Winter January 5, 2015 Towards News Verification: Deception Detection Methods for News Discourse Victoria L. Rubin Niall J. Conroy Yimin Chen Available at: http://works.bepress.com/victoriarubin/6/ Towards News Verification: Deception Detection Methods for News Discourse Victoria L. Rubin, Niall J. Conroy, and Yimin Chen Language and Information Technology Research Lab (LIT.RL) Faculty of Information and Media Studies University of Western Ontario, London, Ontario, CANADA [email protected], [email protected], [email protected] Abstract methods can complement and enhance the notoriously News verification is a process of determining poor human ability to discern truth from deception. whether a particular news report is truthful or A substantial body of the automated deception deceptive. Deliberately deceptive (fabricated) news detection literature seeks to compile, test, and cluster creates false conclusions in the readers’ minds. predictive cues for deceptive messages but discourse Truthful (authentic) news matches the writer’s and pragmatics (the use of language to accomplish knowledge. How do you tell the difference between the communication) has rarely been considered thus far. two in an automated way? To investigate this question, The online news context has received surprisingly we analyzed rhetorical structures, discourse little attention in deception detection compared to other constituent parts and their coherence relations in digital contexts such as deceptive interpersonal e-mail, deceptive and truthful news sample from NPR’s “Bluff fake social network profiles, dating profiles, product the Listener”. Subsequently, we applied a vector space reviews or fudged online resumes. It is, however, model to cluster the news by discourse feature important to automatically identify and flag fake, similarity, achieving 63% accuracy. Our predictive fabricated, phony press releases, and hoaxes. Such model is not significantly better than chance (56% automated news verification systems offer a promise of accuracy), though comparable to average human lie minimizing deliberate misinformation in the news detection abilities (54%). Methodological limitations flow. Here we take a first step towards such news and future improvements are discussed. The long-term verification system. goal is to uncover systematic language differences and inform the core methodology of the news verification 1.1. Research Objectives system. This research aims to enable the identification of deliberately deceptive information in text-based online news. Our immediate target is the ability to make 1. Introduction predictions about each previously unseen news piece: Mistaking fake news for authentic reports can have is it likely to belong to the truthful or deceptive costly consequences, as being misled or misinformed category? A news verification system based on the negatively impacts our decision-making and its methodology can alert users to potentially deceptive consequent outcomes. Fake, fabricated, falsified, news in the incoming news stream and prompt users to disingenuous, or misleading news reports constitute further fact-check suspicious instances. It is an instances of digital deception or deliberate information system support for critical news analysis in misinformation. “Digital deception”, a term signifying everyday or professional information-seeking and use. deception in the context of information and communication technology, is defined here as an 1.2. Problem Statement Elaboration intentional control of information in a technologically 1.2.1. News Context. Daily news constitutes an mediated environment to create a false belief or false important source of information for our everyday and conclusion [1]. Few news verification mechanisms professional lives. News can affect our personal currently exist in the context of online news, decisions on matters such as investments, health, disseminated via either institutional or non-institutional online purchasing, legal matters, travel or recreation. channels, or provided by news aggregators or news Professionals analysts (for instance, in finances, stock archives. The sheer volume of the information requires market, business, or government intelligence) sift novel automated approaches. Automatic analytical through vast amounts of news to discover facts, reveal patterns, and make future forecasts. Digital news – electronically delivered online articles – is easily accessible nowadays either via news source websites, mistaken for authentic report, and it demonstrates the or by keyword searching in search engines, or via news very significant negative consequences such errors can feed aggregation sites and services that pull together create. More recently, the 2013 Boston Marathon users’ subscription feeds and deliver them to personal terrorist attack “evoked an outpouring of citizen computers or mobile devices (e.g., drudgereport.com, journalism” with charity scams and false rumors about newsblur.com, huffingtonpost.com, bloglines.com). who the killers were [6]. Other examples of companies Online news sources, however, range in credibility – “struck by phony press releases” include the fiber optic from well-established institutional mainstream media manufacturer, Emulex, and Aastrom Biosciences [7]. websites (e.g., npr.org, bbc.com, cbc.ca) to the non- institutional websites of amateur reporters or citizen 1.2.4. Motivations to Deceive and Misinform. Why journalists (e.g., the CNN’s iReport.com, thirdreport. would anyone bother falsifying information in the com, allvoices.com, and other social media channels news? Several driving forces are apparent: a) to and their archives). maximize one’s gains, reputation, or expertise; or b) to 1.2.2. Citizen Journalism Context. The mis- minimize the reputation of others (people or information problem [2] is exacerbated in the current organizations) by decreasing their ratings or environment of user-contributed news. “An increasing trustworthiness. One of the more legitimate reasons is number of media distributors relies on contributions c) to set up copyright traps for detecting plagiarism or from amateur reporters producing authentic materials copyright infringement. For instance, the ANP in the on the spot, e.g., in cases of natural disasters or Netherlands once deliberately included a false story political disturbances. With mobile devices it is easy to about a fire in their radio newscast to verify if Radio forge media on the spot of capturing and publishing Veronica really had stolen its news from the ANP. them. Thus, it is increasingly harder to determine the Several hours later, Radio Veronica also aired the story originality and quality of delivered media, especially [8]. Reputable sources may declare their intentions to under the constant pressure to be first on the news fabricate news, but the news may still be misconstrued market” [3]. Citizen journalists are not obliged to as genuine. The Chicago youth magazine, Muse, for follow the guidelines of source-checking and fact- instance, regularly includes a two-page spread of checking cultivated in professional journalism, now science and technology news, with one false story for dubbed as “News 1.0” or “the discipline of strict readers to guess [8]. Such deliberately fake news is not verification”. Non-institutional news media, including immediately identifiable, especially when taken out of “citizen journalism” [4] or “News 2.0”, allow context (in digital archives or aggregator sites). unverified posts to pass for bona-fide reporting. In many cases, the news produced by citizen journalists is 2. Literature Review reliable and verified, but there have been cases in 2.1. Human Abilities to Discern Lies which news has been intentionally faked, both within What is known about human abilities to spot institutional and amateur reporting. The speed and ease deception? Interpersonal Psychology and Communica- by which information can be created and disseminated, tion studies have shown that people are generally not coupled with new mechanisms for news production that successful in distinguishing lies even when they and consumption, require new verification tools are alerted to the possibility [9], [10], [11]. On average, applicable on a large scale. when scored for accuracy of the lie-truth discrimination task people succeed only about half of 1.2.3. Examples of Fabricated News. In October the time [12]. A meta-analytical review of over 100 2008, three years prior to Steve Jobs’ death, a citizen experiments with over 1,000 participants, [13] journalist posted a report falsely stating that Jobs had determined an unimpressive mean accuracy rate of suffered a heart attack and had been rushed to a 54%, slightly above chance [14]. hospital. The original deliberate misinformation was Nonetheless, recent studies that examine quickly “re-tweeted” disregarding the fact that it communicative behaviors suggest that deceivers originated from the CNN’s iReport.com which allows communicate in qualitatively different ways from “unedited, unfiltered” posts. Although the erroneous truth-tellers. In other words, the current theory suggests information was later corrected, the “news” of Jobs’ that there may be stable differences in behaviors of alleged health crisis spread fast, causing confusion and liars versus truth-tellers, and that the differences should uncertainty, and resulting in a rapid fluctuation of his be especially evident in the verbal aspects of behavior company’s

View Full Text

Details

  • File Type
    pdf
  • Upload Time
    -
  • Content Languages
    English
  • Upload User
    Anonymous/Not logged-in
  • File Pages
    12 Page
  • File Size
    -

Download

Channel Download Status
Express Download Enable

Copyright

We respect the copyrights and intellectual property rights of all users. All uploaded documents are either original works of the uploader or authorized works of the rightful owners.

  • Not to be reproduced or distributed without explicit permission.
  • Not used for commercial purposes outside of approved use cases.
  • Not used to infringe on the rights of the original creators.
  • If you believe any content infringes your copyright, please contact us immediately.

Support

For help with questions, suggestions, or problems, please contact us