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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.


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Proceedings ArticleDOI
11 Feb 2012
TL;DR: A website that collected the first large corpus of follower ratings on Twitter updates finds that users value information sharing and random thoughts above me-oriented or presence updates, and offers insight into evolving social norms.
Abstract: While microblog readers have a wide variety of reactions to the content they see, studies have tended to focus on extremes such as retweeting and unfollowing. To understand the broad continuum of reactions in-between, which are typically not shared publicly, we designed a website that collected the first large corpus of follower ratings on Twitter updates. Using our dataset of over 43,000 voluntary ratings, we find that nearly 36% of the rated tweets are worth reading, 25% are not, and 39% are middling. These results suggest that users tolerate a large amount of less-desired content in their feeds. We find that users value information sharing and random thoughts above me-oriented or presence updates. We also offer insight into evolving social norms, such as lack of context and misuse of @mentions and hashtags. We discuss implications for emerging practice and tool design.

120 citations

Journal ArticleDOI
TL;DR: Markedly increased use of the Twitter microblogging platform at recent RSNA annual meetings demonstrates the potential to leverage this technology to engage meeting attendees, improve scientific sessions, and promote improved collaboration at national radiology meetings.
Abstract: Purpose Twitter is a social media microblogging platform that allows rapid exchange of information between individuals. Despite its widespread acceptance and use at various other medical specialty meetings, there are no published data evaluating its use at radiology meetings. The purpose of this study is to quantitatively and qualitatively evaluate the use of Twitter as a microblogging platform at recent RSNA annual meetings. Methods Twitter activity meta-data tagged with official meeting hashtags #RSNA11 and #RSNA12 were collected and analyzed. Multiple metrics were evaluated, including daily and hourly Twitter activity, frequency of microblogging activity over time, characteristics of the 100 most active Twitter users at each meeting, characteristics of meeting-related tweets, and the geographic origin of meeting microbloggers. Results The use of Twitter microblogging increased by at least 30% by all identifiable meaningful metrics between the 2011 and 2012 RSNA annual meetings, including total tweets, tweets per day, activity of the most active microbloggers, and total number of microbloggers. Similar increases were observed in numbers of North American and international microbloggers. Conclusion Markedly increased use of the Twitter microblogging platform at recent RSNA annual meetings demonstrates the potential to leverage this technology to engage meeting attendees, improve scientific sessions, and promote improved collaboration at national radiology meetings.

118 citations

Proceedings ArticleDOI
01 Sep 2016
TL;DR: The analysis of the usage characteristics, content and automatic classification potential of tweets about software applications by using descriptive statistics, content analysis and machine learning techniques shows that tweets provide a valuable input for software companies.
Abstract: Users of the Twitter microblogging platform share a vast amount of information about various topics through short messages on a daily basis. Some of these so called tweets include information that is relevant for software companies and could, for example, help requirements engineers to identify user needs. Therefore, tweets have the potential to aid in the continuous evolution of software applications. Despite the existence of such relevant tweets, little is known about their number and content. In this paper we report on the results of an exploratory study in which we analyzed the usage characteristics, content and automatic classification potential of tweets about software applications by using descriptive statistics, content analysis and machine learning techniques. Although the manual search of relevant information within the vast stream of tweets can be compared to looking for a needle in a haystack, our analysis shows that tweets provide a valuable input for software companies. Furthermore, our results demonstrate that machine learning techniques have the capacity to identify and harvest relevant information automatically.

118 citations

01 Jan 2010
TL;DR: This research-in-progress paper reports on the use of microblogging as a communication and information sharing resource during a recent violent crisis in Seattle-Tacoma area of Washington.
Abstract: This research-in-progress paper reports on the use of microblogging as a communication and information sharing resource during a recent violent crisis. The goal of the larger research effort is to investigate the role that microblogging plays in crisis communication during violent events. The shooting of four police officers and the subsequent 48-hour search for the suspect that took place in the Seattle-Tacoma area of Washington in late November 2009 is used as a case study. A stream of over 6,000 publically available messages on Twitter, a popular microblogging site, was collected and individual messages were categorized as information, opinion, technology, emotion, and action-related. The coding and statistical analyses of the messages suggest that citizens use microblogging as one method to organize and disseminate crisis-related information. Additional research is in progress to analyze the types of information transmitted, the sources of the information, and the temporal trends of information shared.

118 citations

Journal ArticleDOI
TL;DR: Evaluated the performance of two leading open source spell checkers on data taken from the microblogging service Twitter, and the extent to which their accuracy is improved by pre-processing with the database rules and classification system is measured.

117 citations


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