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Microblogging

About: Microblogging is a research topic. Over the lifetime, 4186 publications have been published within this topic receiving 137030 citations. The topic is also known as: microblog.


Papers
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Journal ArticleDOI
TL;DR: It is demonstrated that users providing above average investment advice are retweeted more often and have more followers, which amplifies their share of voice.
Abstract: Microblogging forums have become a vibrant online platform to exchange trading ideas and other stock-related information. Using methods from computational linguistics, we analyze roughly 250,000 stock-related microblogging messages, so-called tweets, on a daily basis. We find the sentiment (i.e., bullishness) of tweets to be associated with abnormal stock returns and message volume to predict next-day trading volume. In addition, we analyze the mechanism leading to efficient aggregation of information in microblogging forums. Our results demonstrate that users providing above average investment advice are retweeted (i.e., quoted) more often and have more followers, which amplifies their share of voice in microblogging forums.

333 citations

Proceedings ArticleDOI
21 Aug 2011
TL;DR: A general and robust machine learning framework for large-scale classification of social media users according to dimensions of interest and encouraging experimental results on 3 tasks with different characteristics are reported.
Abstract: More and more technologies are taking advantage of the explosion of social media (Web search, content recommendation services, marketing, ad targeting, etc.). This paper focuses on the problem of automatically constructing user profiles, which can significantly benefit such technologies. We describe a general and robust machine learning framework for large-scale classification of social media users according to dimensions of interest. We report encouraging experimental results on 3 tasks with different characteristics: political affiliation detection, ethnicity identification and detecting affinity for a particular business.

330 citations

Journal ArticleDOI
TL;DR: It is demonstrated that users providing above average investment advice are retweeted more often and have more followers, which amplifies their share of voice, as well as disagreement and volatility in microblogging forums.
Abstract: Microblogging forums (e.g., Twitter) have become a vibrant online platform for exchanging stock-related information. Using methods from computational linguistics, we analyse roughly 250,000 stock-related messages (so-called tweets) on a daily basis. We find an association between tweet sentiment and stock returns, message volume and trading volume, as well as disagreement and volatility. In contrast to previous related research, we also analyse the mechanism leading to an efficient aggregation of information in microblogging forums. Our results demonstrate that users providing above average investment advice are retweeted (i.e., quoted) more often and have more followers, which amplifies their share of voice.

327 citations

Journal ArticleDOI
TL;DR: The most popular Canadian political hashtag, #cdnpoli, has been analyzed in this paper, where the authors analyze the intersection of micro blogging and Canadian politics, and find that #iranelection was the number one news topic on Twitter in 2009.
Abstract: Twitter is the latest social networking tool said to be reshaping politics. Twitter allows subscribers to write a 140-character status update, called a ‘tweet'. This research analyzes the intersection of microblogging and Canadian politics. There is little scholarship on the political aspects of Twitter. This paper seeks to fill this gap through a content analysis of the most popular Canadian political hashtag, #cdnpoli. Designated by a ‘hash' symbol (#), a hashtag is a keyword assigned to information that describes a tweet and aides in searching. With 50 million tweets per day, hashtags are central to organizing information on Twitter. Hashtags organize discussion around specific topics or events. Political hashtags came to prominence in events like the 2009 Iran presidential election. Indeed, #iranelection was the number one news topic on Twitter in 2009. The popular literature suggests that Twitter is a democratic media because it allows for on-the-ground reporting of breaking news and democratic activ...

327 citations

Proceedings ArticleDOI
13 Jun 2010
TL;DR: The micro-meme phenomenon is described and the importance of this new tagging practice for the larger real-time search context is discussed: emergent topics for which a tag is created, used widely for a few days, then disappears.
Abstract: Users on Twitter, a microblogging service, started the phenomenon of adding tags to their messages sometime around February 2008. These tags are distinct from those in other Web 2.0 systems because users are less likely to index messages for later retrieval. We compare tagging patterns in Twitter with those in Delicious to show that tagging behavior in Twitter is different because of its conversational, rather than organizational nature. We use a mixed method of statistical analysis and an interpretive approach to study the phenomenon. We find that tagging in Twitter is more about filtering and directing content so that it appears in certain streams. The most illustrative example of how tagging in Twitter differs is the phenomenon of the Twitter micro-meme: emergent topics for which a tag is created, used widely for a few days, then disappears. We describe the micro-meme phenomenon and discuss the importance of this new tagging practice for the larger real-time search context.

326 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023202
2022551
2021153
2020238
2019226
2018282