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Discriminating Gender on Twitter

by John D. Burger, John Henderson, George Kim, Guido Zarrella
"... Accurate prediction of demographic attributes from social media and other informal online content is valuable for marketing, personalization, and legal investigation. This paper describes the construction of a large, multilingual dataset labeled with gender, and investigates statistical models for d ..."
Abstract - Cited by 64 (0 self) - Add to MetaCart
for determining the gender of uncharacterized Twitter users. We explore several different classifier types on this dataset. We show the degree to which classifier accuracy varies based on tweet volumes as well as when various kinds of profile metadata are included in the models. We also perform a large

Suspended Accounts In Retrospect: An Analysis of Twitter Spam

by Kurt Thomas, Chris Grier, Vern Paxson, Dawn Song - In Proc. of 11th IMC , 2011
"... In this study, we examine the abuse of online social networks at the hands of spammers through the lens of the tools, techniques, and support infrastructure they rely upon. To perform our analysis, we identify over 1.1 million accounts suspended by Twitter for disruptive activities over the course o ..."
Abstract - Cited by 74 (6 self) - Add to MetaCart
of seven months. In the process, we collect a dataset of 1.8 billion tweets, 80 million of which belong to spam accounts. We use our dataset to characterize the behavior and lifetime of spam accounts, the campaigns they execute, and the wide-spread abuse of legitimate web services such as URL shorteners

Evaluation Datasets for Twitter Sentiment Analysis A survey and a new dataset, the STS-Gold

by Hassan Saif, Miriam Fern, Yulan He, Harith Alani
"... Abstract. Sentiment analysis over Twitter offers organisations and individuals a fast and effective way to monitor the publics ’ feelings towards them and their competitors. To assess the performance of sentiment analysis methods over Twitter a small set of evaluation datasets have been released in ..."
Abstract - Cited by 13 (4 self) - Add to MetaCart
Abstract. Sentiment analysis over Twitter offers organisations and individuals a fast and effective way to monitor the publics ’ feelings towards them and their competitors. To assess the performance of sentiment analysis methods over Twitter a small set of evaluation datasets have been released

Evaluating Event Credibility on Twitter

by Manish Gupta, Peixiang Zhao, Jiawei Han , 2012
"... Though Twitter acts as a realtime news source with people acting as sensors and sending event updates from all over the world, rumors spread via Twitter have been noted to cause considerable damage. Given a set of popular Twitter events along with related users and tweets, we study the problem of au ..."
Abstract - Cited by 16 (3 self) - Add to MetaCart
Though Twitter acts as a realtime news source with people acting as sensors and sending event updates from all over the world, rumors spread via Twitter have been noted to cause considerable damage. Given a set of popular Twitter events along with related users and tweets, we study the problem

Whom You Know Matters: Venture Capital Networks and Investment Performance,

by Yael Hochberg , Alexander Ljungqvist , Yang Lu , Steve Drucker , Jan Eberly , Eric Green , Yaniv Grinstein , Josh Lerner , Laura Lindsey , Max Maksimovic , Roni Michaely , Maureen O'hara , Ludo Phalippou Mitch Petersen , Jesper Sorensen , Per Strömberg Morten Sorensen , Yael Hochberg , Johnson - Journal of Finance , 2007
"... Abstract Many financial markets are characterized by strong relationships and networks, rather than arm's-length, spot-market transactions. We examine the performance consequences of this organizational choice in the context of relationships established when VCs syndicate portfolio company inv ..."
Abstract - Cited by 138 (8 self) - Add to MetaCart
are simply the ones with better past performance records: While we do find evidence of persistence in performance from one fund to the next, our measures of network centrality continue to have a positive and significant effect on fund exit rates when we control for persistence. The way we construct

HybridRank: Ranking in the Twitter Hybrid Networks

by Jianyu Li
"... User influence in social media may depend on multiple modes of communication. Research has identified the importance of a hybrid network on Twitter, comprising of the follower, retweet and mention networks. HybridRank is an extension of PageRank which considers all three networks. Using a longitudin ..."
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longitudinal panel dataset of 8K Twitter users, we evalu-ated the performance of HybridRank and predicted the in-fluence of users. We used the number of times that a user was retweeted or mentioned as a proxy for influence. Hy-bridRank outperforms a (good) baseline method for men-tions outside the focal user’s

Community Discovery in Twitter Based on User Interests

by Yang Zhang , Yao Wu , Qing Yang - Journal of Computational Information Systems , 2012
"... Abstract Twitter has recently emerged as a popular social microblogging service. There are over 100 million users in Twitter nowadays, little is known yet about Twitter at user level. In this paper, we investigate the problem of identifying communities in Twitter based on users' interests. To ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
". Experimental results show that our method can successfully discover communities in Twitter, and gives a much better performance than random selection. From a side view, our experiment also shows that users in our dataset of Twitter can be approximately categorized into 400 communities.

The Impact of Network Structure on Breaking Ties in Online Social Networks: Unfollowing on Twitter

by Funda Kivran-swaine, Priya Govindan, Mor Naaman
"... We investigate the breaking of ties between individuals in the online social network of Twitter, a hugely popular social media service. Building on sociology concepts such as strength of ties, embeddedness, and status, we explore how network structure alone influences tie breaks – the common phenome ..."
Abstract - Cited by 12 (0 self) - Add to MetaCart
phenomena of an individual ceasing to “follow” another in Twitter’s directed social network. We examine these relationships using a dataset of 245,586 Twitter “follow ” edges, and the persistence of these edges after nine months. We show that structural properties of individuals and dyads at Time 1 have a

The long-run impact of bombing Vietnam

by ♦ Edward Miguel , Gérard Roland , Patrick Keane , Benjamin Reich , Michael Sheinkman , Bill Shaw , Tom Smith Pamela Jakiela , Melissa Knox , Khuyen Nguyen , Rachel Polimeni , Monika Shah , Fred Brown , Jim Fearon , Raquel Fernandez , Scott Gartner , Steve Helfand , Chang-Tai Hsieh , Chad Jones , Dean Karlan , David Laitin , Adam Przeworski - Journal of Development Economics , 2011
"... Abstract: We investigate the impact of U.S. bombing on later economic development in Vietnam. The Vietnam War featured the most intense bombing campaign in military history and had massive humanitarian costs. We use a unique U.S. military dataset containing bombing intensity at the district level ( ..."
Abstract - Cited by 92 (3 self) - Add to MetaCart
Abstract: We investigate the impact of U.S. bombing on later economic development in Vietnam. The Vietnam War featured the most intense bombing campaign in military history and had massive humanitarian costs. We use a unique U.S. military dataset containing bombing intensity at the district level

Self-disclosure topic model for classifying and analyzing Twitter conversations

by Jinyeong Bak, Chin-yew Lin
"... Self-disclosure, the act of revealing one-self to others, is an important social be-havior that strengthens interpersonal rela-tionships and increases social support. Al-though there are many social science stud-ies of self-disclosure, they are based on manual coding of small datasets and ques-tionn ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
-tionnaires. We conduct a computational analysis of self-disclosure with a large dataset of naturally-occurring conversa-tions, a semi-supervised machine learning algorithm, and a computational analysis of the effects of self-disclosure on subse-quent conversations. We use a longitu-dinal dataset of 17 million
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