Our system is also able to predict ~ 25% of the correct case of merges within the first month of the merge and ~ 40% of the cases within a year.
In this paper, we develop a content-cum-user based deep learning framework DeepTagRec to recommend appropriate question tags on Stack Overflow.
In particular, we observe that the choice to post the question as anonymous is dependent on the user's perception of anonymity and they often choose to speak about depression, anxiety, social ties and personal issues under the guise of anonymity.
In this paper, we create and release the first ever dataset for counterspeech using comments from YouTube.
Social and Information Networks
Word senses are not static and may have temporal, spatial or corpus-specific scopes.
We propose ENWalk, a framework to detect the spammers by learning the feature representations of the users in the social media.
Notably, features representing the language use patterns of the users are most discriminative and alone account for an accuracy of 74. 18%.
Language in social media is mostly driven by new words and spellings that are constantly entering the lexicon thereby polluting it and resulting in high deviation from the formal written version.