Neural Based Statement Classification for Biased Language

Biased language commonly occurs around topics which are of controversial nature, thus, stirring disagreement between the different involved parties of a discussion. This is due to the fact that for language and its use, specifically, the understanding and use of phrases, the stances are cohesive within the particular groups. However, such cohesiveness does not hold across groups. In collaborative environments or environments where impartial language is desired (e.g. Wikipedia, news media), statements and the language therein should represent equally the involved parties and be neutrally phrased. Biased language is introduced through the presence of inflammatory words or phrases, or statements that may be incorrect or one-sided, thus violating such consensus. In this work, we focus on the specific case of phrasing bias, which may be introduced through specific inflammatory words or phrases in a statement. For this purpose, we propose an approach that relies on a recurrent neural networks in order to capture the inter-dependencies between words in a phrase that introduced bias. We perform a thorough experimental evaluation, where we show the advantages of a neural based approach over competitors that rely on word lexicons and other hand-crafted features in detecting biased language. We are able to distinguish biased statements with a precision of P=0.92, thus significantly outperforming baseline models with an improvement of over 30%. Finally, we release the largest corpus of statements annotated for biased language.Comment: The Twelfth ACM International Conference on Web Search and Data Mining, February 11--15, 2019, Melbourne, VIC, Australi

The effects of native advertising on audience perceptions of legacy and online news publishers

Extending research from Wojdynski and Evans, this experimental study replicates the challenges of effectively disclosing native advertising to readers and demonstrates a promising inoculation method that increases likelihood of recognition. Moreover, this quantitative research indicates that both legacy and online news publishers were evaluated less favorably for displaying native advertising. Attitudes toward the publisher and perceptions of its credibility declined for both, although online publishers suffered greater attitudinal damage than did legacy publishers who may benefit from their established reputation

Reading between the lines : is news media in Fiji supporting or challenging gender stereotypes? : a frame analysis of local news media coverage of violence against women during the 16 Days of Activism against Gender-based Violence campaign of 2017

Violence against women is recognised as a global public health issue and an obstacle to development, as ending it is inextricably linked with achieving gender equality. The public relies on and believes in the capacity of news media to present them with a ‘true’ picture of reality and the news media are therefore treated as valuable allies in changing the norms, beliefs and attitudes that perpetuate violence against women. In the production and consumption of news, however, journalists employ frames to condense complex events into interesting and appealing news reports, in turn influencing how audiences view particular events, activities and issues, especially when it comes to attributing blame and responsibility. This study employs a frame analysis to identify whether, and to what extent, episodic or thematic framing is used in news articles on violence against women published in the Fiji Sun and Fiji Times during and around the 16 Days of Activism against Gender-based Violence campaign of 2017. It showed that episodic framing was overwhelmingly used in the sample, thereby divorcing the violence from its social roots and encouraging audiences to blame the individuals involved, both for the violence itself and for remedying it. This directly contradicts the campaign’s central principles positioning violence against women as a social and development issue that requires every member of society to play a part in ending it. The results, therefore, suggest that changes are needed in how organisations engage with the news media to ensure that coverage of violence against women improves in both quantity and quality

Internet Information and Communication Behavior during a Political Moment: The Iraq War, March 2003

This article explores the Internet as a resource for political information and communication in March 2003, when American troops were first sent to Iraq, offering us a unique setting of political context, information use, and technology. Employing a national survey conducted by the Pew Internet & American Life project. We examine the political information behavior of the Internet respondents through an exploratory factor analysis; analyze the effects of personal demographic attributes and political attitudes, traditional and new media use, and technology on online behavior through multiple regression analysis; and assess the online political information and communication behavior of supporters and dissenters of the Iraq War. The factor analysis suggests four factors: activism, support, information seeking, and communication. The regression analysis indicates that gender, political attitudes and beliefs, motivation, traditional media consumption, perceptions of bias in the media, and computer experience and use predict online political information behavior, although the effects of these variables differ for the four factors. The information and communication behavior of supporters and dissenters of the Iraq War differed significantly. We conclude with a brief discussion of the value of "interdisciplinary poaching" for advancing the study of Internet information practices