2019
DOI: 10.1108/ajim-08-2019-0204
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The topic of terrorism on Yahoo! Answers: questions, answers and users’ anonymity

Abstract: Purpose The purpose of this paper is to explore the use of community question answering sites (CQAs) on the topic of terrorism. Three research questions are investigated: what are the dominant themes reflected in terrorism-related questions? How do answer characteristics vary with question themes? How does users’ anonymity relate to question themes and answer characteristics? Design/methodology/approach Data include 300 questions that attracted 2,194 answers on the community question answering Yahoo! Answers… Show more

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Cited by 8 publications
(7 citation statements)
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“…There are other useful and inspiring attempts at a universal definition reached through a process of characterizing the toxicity of comments [34,35], or utilizing context information [36,37].…”
Section: Definitions Of Hate Speechmentioning
confidence: 99%
“…There are other useful and inspiring attempts at a universal definition reached through a process of characterizing the toxicity of comments [34,35], or utilizing context information [36,37].…”
Section: Definitions Of Hate Speechmentioning
confidence: 99%
“…This study further judged the importance of features based on the value of chi-square statistics (Chua and Banerjee, 2019). On the surface features, “lack of meta-information” (203.117 *** −342.315 *** ) was a very important feature of health misinformation, and “stitching pictures” (155.753 *** −200.180 *** ), “layout disorder” (121.088 *** −176.690 *** ) and “misspelled words” (93.119 *** −110.088 *** ) were relatively important features of health misinformation.…”
Section: Resultsmentioning
confidence: 99%
“…Core features were coded as a source if it surrounded the incredibility of the information source, such as “fake authority”, “unidentified sources”, “absence of exact evidence”, etc. The robustness of the coding scheme was confirmed by checking that each health misinformation could be coded into one or more features (Chua and Banerjee, 2019). The specific coding results and its description are shown in Table 1.…”
Section: Methodsmentioning
confidence: 99%
“…To accommodate different user needs and preferences, social Q&A communities offer various identity options (Chua & Banerjee, 2020). These identity options include real names, pseudonymity, and anonymity, which differ in the level of personal disclosure required (Guo & Caine, 2021).…”
Section: Anonymitymentioning
confidence: 99%