Twitter Lists Research Articles

Evolution of a search: the use of dynamic twitter searches during superstorm sandy.

Background: Twitter has emerged as a critical source of free and openly available information during emergency response operations, providing an unmatched level of on-the-ground situational awareness in real-time. Responders and survivors turn to Twitter to share information and resources within communities, conduct rumor control, and provide a “boots on the ground” understanding of the disaster. However, the ability to tune out background “noise” is essential to effectively utilizing Twitter to identify important and useful information during an emergency response. Methods: This article highlights a two-prong strategy in which the use of a Twitter list paired with subject specific Boolean searches provided increased situational awareness and early event detection during the United States Department of Health and Human Services (HHS), Office of the Assistant Secretary for Preparedness and Response (ASPR) response to Superstorm Sandy in 2012. To maximize the amount of relevant information that was retrieved, the Twitter list and Boolean searches were dynamic and responsive to real-time developments, evolving health threats, and the informational needs of decision-makers. Conclusion: The use of a Twitter list combined with Boolean searches led to enhanced situational awareness throughout the HHS response. The incorporation of a dynamic search strategy over the course of the HHS Sandy response, allowed for the ability to account for over-tweeted information, changes in event related conversation, and decreases in the return of relevant information.

Tagging users based on Twitter lists

This paper addresses the problem of tagging users in Twitter, one of the most popular microblogs. Although there are an enormous number of Twitter users, some are particularly influential regarding certain topics (e.g., politics, sports). These users often transmit useful information about their topics. For example, a user familiar with political issues often transmits useful information about the latest political news. To obtain useful information, therefore, it is very important to know these user topics. To discover user topics, we propose a user tagging method using Twitter lists, the official Twitter function for making and sharing user lists. From our observations, users included in the same list were likely to have posted on the same topic. This topic was often described by the list name. For example, the list named 'politicians-list' has politicians as its members. For this reason, our proposed method regards list names as sequences of tags and assigns them to list members. Experiments conducted using two datasets showed that our proposed method works effectively in the user profiling domain and the user ranking domain.