Testing the event witnessing status of micro-bloggers from evidence in their micro-blogs

Abstract

This paper demonstrates a framework of processes for identifying potential witnesses of events from evidence they post to social media. The research defines original evidence models for micro-blog content sources, the relative uncertainty of different evidence types, and models for testing evidence by combination. Methods to filter and extract evidence using automated and semi-automated means are demonstrated using a Twitter case study event. Further, an implementation to test extracted evidence using Dempster Shafer Theory of Evidence are presented. The results indicate that the inclusion of evidence from micro-blog text and linked image content can increase the number of micro-bloggers identified at events, in comparison to the number of micro-bloggers identified from geotags alone. Additionally, the number of micro-bloggers that can be tested for evidence corroboration or conflict, is increased by incorporating evidence identified in their posting history.

Mining social media for newsgathering: A review

“…They define four types of accounts: (1) witness accounts, or accounts reporting a direct observation of the event or its effects, (2) impact accounts, or those being directly impacted or taking direct action because of the event and/or its effects, (3) relay accounts, in which a micro-blogger relays a witness or impact account, and (4) other accounts, which are users relevant to the event, but do not fall in any of the other three categories. Besides textual content, [84,85] used geotags and image features to perform supervised classification of users as witnesses or non-witnesses. They used unigrams, bigrams and part-of-speech tags as textual features.…”