Koustav Rudra

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Linguistic research on multilingual societies has indicated that there is usually a preferred language for expression of emotion and sentiment (Dewaele, 2010). Paucity of data has limited such studies to participant interviews and speech transcriptions from small groups of speakers. In this paper, we report a study on 430,000 unique tweets from Indian(More)
Microblogging sites such as Twitter and Weibo are increasingly being used to enhance situational awareness during various natural and man-made disaster events such as floods, earthquakes, and bomb blasts. During any such event, thousands of microblogs (tweets) are posted in short intervals of time. Typically, only a small fraction of these tweets contribute(More)
Microblogging sites like Twitter have become important sources of real-time information during disaster events. A significant amount of valuable <i>situational information</i> is available in these sites; however, this information is immersed among hundreds of thousands of tweets, mostly containing sentiments and opinion of the masses, that are posted(More)
During mass convergence events such as natural disasters, microblogging platforms like Twitter are widely used by affected people to post situational awareness messages. These crisis-related messages disperse among multiple categories like infrastructure damage, information about missing, injured, and dead people etc. The challenge here is to extract(More)
To help users find popular topics of discussion, Twitter periodically publishes 'trending topics' (trends) which are the most discussed keywords (e.g., hashtags) at a certain point of time. Inspection of the trends over several months reveals that while most of the trends are related to events in the off-line world, such as popular television shows, sports(More)
Millions of microblogs are posted during disasters, which include not only information about the present situation, but also the emotions / opinions of the masses. While most of the prior research has been on extracting situational information, this work focuses on a particular type of non-situational tweets - communal tweets, i.e., abusive posts targeting(More)
The use of microblogging platforms such as Twitter during crises has become widespread. More importantly, information disseminated by affected people contains useful information like reports of missing and found people, requests for urgent needs etc. For rapid crisis response, humanitarian organizations look for situa-tional awareness information to(More)
Swearing is a prevalent phenomenon, in regular conversations as well as on social media. Whether multilinguals have a preference for a language while swearing and if so, what factors influence it, is an interesting question that has intrigued linguists, but large scale studies of multilingual swearing behavior has been impossible due to unavailability of(More)