This paper describes a new shared task for humor understanding that attempts to eschew the ubiquitous binary approach to humor detection and focus on comparative humor ranking instead. The task is based on a new dataset of funny tweets posted in response to shared hashtags, collected from the ‘Hashtag Wars’ segment of the TV show @midnight. The results are evaluated in two subtasks that require...

This paper investigates Twitter usage in scientific contexts, particularly the use of Twitter during scientific conferences. It proposes a methodology for capturing and analyzing citations/references in Twitter. First results are presented based on the analysis of tweets gathered for two conference hashtags.

Arguably one of the most important features of Twitter is the support for“retweets”or messages re-posted verbatim by a user that were originated by someone else. (This does not include modified tweets that sometimes are referred to as retweets.) Despite the fact that retweets are routinely studied and reported, many important questions remain about user motivation for their use and their signif...

In this paper, we build a generic opinion-fact classifier to detect opinions and facts from online news articles and social media datasets such as Youtube comments and idiom hashtags. We further use this classification model to compare opinionatedness of various news article sections. The proposed classifier produces better results than the existing methods over four different datasets, and the...

The problem to accurately and parsimoniously characterize random series of events (RSEs) present in the Web, such as e-mail conversations or Twitter hashtags, is not trivial. Reports found in the literature reveal two apparent conflicting visions of how RSEs should be modeled. From one side, the Poissonian processes, of which consecutive events follow each other at a relatively regular time and...

While social media research has provided detailed cumulative analyses of selected social media platforms and content, especially Twitter, newer platforms, apps, and visual content have been less extensively studied so far. This paper proposes a methodology for studying Instagram activity, building on established methods for Twitter research by initially examining hashtags, as common structural ...

In our first-ever appearance at TREC, we explore initial ideas on building an effective search tool over tweet stream as a participation in this year’s microblog track. Among those ideas are tweet expansion with short representation of terms that frequently co-occur with hashtags and URLs, and re-ranking based on statistics that estimate user popularity (using replies and mentions), tweet popul...

Twitter spam accounts try to spread malicious content, deceive or advertise certain thoughts over Twitter network. Different approaches have been presented both in industry and academia to identify spammers on Twitter. This study aims at understanding the behavior of Twitter spam accounts targeting Saudi Arabia. In this study the author performs an empirical analysis of Twitter spam accounts in...

Twitter users demonstrate many characteristics via their online presence. Connections, community memberships, and communication patterns reveal both idiosyncratic and general properties of users. In addition, the content of tweets can be critical for distinguishing the role and importance of a user. In this work, we explore Twitter user classification using context and content cues. We construc...