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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: Experiments show that the proposals can be used efficiently to improve unsupervised and supervised link prediction task in a directed and asymmetric large-scale network, such as Twitter.
Abstract: Currently, online social networks and social media have become increasingly popular showing an exponential growth. This fact have attracted increasing research interest and, in turn, facilitating the emergence of new interdisciplinary research directions, such as social network analysis. In this scenario, link prediction is one of the most important tasks since it deals with the problem of the existence of a future relation among members in a social network. Previous techniques for link prediction were based on structural (or topological) information. Nevertheless, structural information is not enough to achieve a good performance in the link prediction task on large-scale social networks. Thus, the use of additional information, such as interests or behaviors that nodes have into their communities, may improve the link prediction performance. In this paper, we analyze the viability of using a set of simple and non-expensive techniques that combine structural with community information for predicting the existence of future links in a large-scale online social network, such as Twitter. Twitter, a microblogging service, has emerged as a useful source of informative data shared by millions of users whose relationships require no reciprocation. Twitter network was chosen because it is not well understood, mainly due to the occurrence of directed and asymmetric links yet. Experiments show that our proposals can be used efficiently to improve unsupervised and supervised link prediction task in a directed and asymmetric large-scale network.

67 citations

Proceedings ArticleDOI
12 Apr 2010
TL;DR: Twitter is used in the governmental context not only for engaging stakeholders in conversation, but for building relationships by creating a social presence with these constituents, enabling many novel and powerful uses for government applications.
Abstract: This research explores the adoption of Twitter by government organizations in the U.S. The recent growth of Twitter by government organizations makes it appear to be in the early adopter stage. As different government agencies utilize Twitter to extend their outreach to specific audiences, one finds novel uses for this communication medium. Since Twitter is designed to deliver short messages with a personal tone, extended conversations in which fragments of information about the users are revealed enable this channel to communicate the social presence of the users. Twitter is used in the governmental context not only for engaging stakeholders in conversation, but for building relationships by creating a social presence with these constituents. In addition to providing a status update and conversation, Twitter can be used for reporting news, sharing information, providing information sources, and coordinating projects. Since Twitter is easily accessed by wireless devices, the reach of this medium is expanded. In all, Twitter is a unique new medium enabling many novel and powerful uses for government applications.

67 citations

Proceedings ArticleDOI
01 May 2013
TL;DR: This work proposes a novel approach to identify a subset of active users during a crisis who can be tracked for fast access to information by user identification along two dimensions: user's location and the user's affinity towards topics of discussion.
Abstract: Social media is gaining popularity as a medium of communication before, during, and after crises. In several recent disasters, it has become evident that social media sites like Twitter and Facebook are an important source of information, and in cases they have even assisted in relief efforts. We propose a novel approach to identify a subset of active users during a crisis who can be tracked for fast access to information. Using a Twitter dataset that consists of 12.9 million tweets from 5 countries that are part of the "Arab Spring" movement, we show how instant information access can be achieved by user identification along two dimensions: user's location and the user's affinity towards topics of discussion. Through evaluations, we demonstrate that users selected by our approach generate more information and the quality of the information is better than that of users identified using state-of-the-art techniques.

66 citations

Journal ArticleDOI
TL;DR: The combined content-analysis (CCA) model is proposed as a useful framework that provides a straightforward approach to guide Twitter-driven studies and that adds rigor to health care social media investigations.
Abstract: Background: Twitter’s 140-character microblog posts are increasingly used to access information and facilitate discussions among health care professionals and between patients with chronic conditions and their caregivers. Recently, efforts have emerged to investigate the content of health care-related posts on Twitter. This marks a new area for researchers to investigate and apply content analysis (CA). In current infodemiology, infoveillance and digital disease detection research initiatives, quantitative and qualitative Twitter data are often combined, and there are no clear guidelines for researchers to follow when collecting and evaluating Twitter-driven content. Objective: The aim of this study was to identify studies on health care and social media that used Twitter feeds as a primary data source and CA as an analysis technique. We evaluated the resulting 18 studies based on a narrative review of previous methodological studies and textbooks to determine the criteria and main features of quantitative and qualitative CA. We then used the key features of CA and mixed-methods research designs to propose the combined content-analysis (CCA) model as a solid research framework for designing, conducting, and evaluating investigations of Twitter-driven content. Methods: We conducted a PubMed search to collect studies published between 2010 and 2014 that used CA to analyze health care-related tweets. The PubMed search and reference list checks of selected papers identified 21 papers. We excluded 3 papers and further analyzed 18. Results: Results suggest that the methods used in these studies were not purely quantitative or qualitative, and the mixed-methods design was not explicitly chosen for data collection and analysis. A solid research framework is needed for researchers who intend to analyze Twitter data through the use of CA. Conclusions: We propose the CCA model as a useful framework that provides a straightforward approach to guide Twitter-driven studies and that adds rigor to health care social media investigations. We provide suggestions for the use of the CCA model in elder care-related contexts. [J Med Internet Res 2016;18(3):e60]

66 citations

Journal ArticleDOI
TL;DR: It was discovered that Twitter has positive impact on informal learning, class dynamics, motivation, as well as the academic and psychological development of young students.
Abstract: Twitter is a well-known Web 20 microblogging social networking site that is quite popular for organizing events and sharing updates It provides just in time communication, social connectivity and immediate feedback through Web, smartphones, tablet PCs, etc The use of Twitter has also attracted educators and researchers due to its growing popularity among students, teachers, and academic communities as a whole This study provides a critical review of Twitter use in educational settings By practicing a systematic research methodology in the selection and review of literature, different pedagogical and instructional benefits and drawbacks of Twitter use in education were discussed Based on these discussions, it was discovered that Twitter has positive impact on informal learning, class dynamics, motivation, as well as the academic and psychological development of young students However, the potential long-term impact of Twitter on academic performance of students and its long-term effect on learning is still worth investigating

66 citations


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