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.

Social Big-Data-Based Content Dissemination in Internet of Vehicles

Abstract: By analogy with Internet of things, Internet of vehicles (IoV) that enables ubiquitous information exchange and content sharing among vehicles with little or no human intervention is a key enabler for the intelligent transportation industry. In this paper, we study how to combine both the physical and social layer information for realizing rapid content dissemination in device-to-device vehicle-to-vehicle (D2D-V2V)-based IoV networks. In the physical layer, headway distance of vehicles is modeled as a Wiener process, and the connection probability of D2D-V2V links is estimated by employing the Kolmogorov equation. In the social layer, the social relationship tightness that represents content selection similarities is obtained by Bayesian nonparametric learning based on real-world social big data, which are collected from the largest Chinese microblogging service Sina Weibo and the largest Chinese video-sharing site Youku. Then, a price-rising-based iterative matching algorithm is proposed to solve the formulated joint peer discovery, power control, and channel selection problem under various quality-of-service requirements. Finally, numerical results demonstrate the effectiveness and superiority of the proposed algorithm from the perspectives of weighted sum rate and matching satisfaction gains.

Why do People Retweet? Anti-Homophily Wins the Day!

Abstract: Twitter and other microblogs have rapidly become a significant means by which people communicate with the world and each other in near realtime. There has been a large number of studies surrounding these social media, focusing on areas such as information spread, various centrality measures, topic detection and more. However, one area which has not received much attention is trying to better understand what information is being spread and why it is being spread. This work looks to get a better understanding of what makes people spread information in tweets or microblogs through the use of retweeting. Several retweet behavior models are presented and evaluated on a Twitter data set consisting of over 768,000 tweets gathered from monitoring over 30,000 users for a period of one month. We evaluate the proposed models against each user and show how people use different retweet behavior models. For example, we find that although users in the majority of cases do not retweet information on topics that they themselves Tweet about as or from people who are "like them" (hence anti-homophily), we do find that models which do take homophily, or similarity, into account fits the observed retweet behaviors much better than other more general models which do not take this into account. We further find that, not surprisingly, people's retweeting behavior is better explained through multiple different models rather than one model.

Analyzing and predicting viral tweets

Abstract: Twitter and other microblogging services have become indispensable sources of information in today's web. Understanding the main factors that make certain pieces of information spread quickly in these platforms can be decisive for the analysis of opinion formation and many other opinion mining tasks.This paper addresses important questions concerning the spread of information on Twitter. What makes Twitter users retweet a tweet? Is it possible to predict whether a tweet will become "viral", i.e., will be frequently retweeted? To answer these questions we provide an extensive analysis of a wide range of tweet and user features regarding their influence on the spread of tweets. The most impactful features are chosen to build a learning model that predicts viral tweets with high accuracy. All experiments are performed on a real-world dataset, extracted through a public Twitter API based on user IDs from the TREC 2011 microblog corpus.

Geographic Dissection of the Twitter Network

Abstract: Geography plays an important role in shaping societal interactions in the offline world. However, as more and more social interactions occur online via social networking sites like Twitter and Facebook, users can interact with others unconstrained by their geolocations, raising the question: does offline geography still matter in online social networks? In this paper, we attempt to address this question by dissecting the Twitter social network based on users’ geolocations and investigating how users’ geolocation impacts their participation in Twitter, including their connections to others and the information they exchange with them. Our in-depth analysis reveals that geography continues to have a significant impact on user interactions in the Twitter social network. The influence of geography could be potentially explained by the shared national, linguistic, and cultural backgrounds of users from the same geographic neighborhood.

Investigating the Community of Practice of World Language Educators on Twitter

Abstract: This study investigated how an online community of teachers engaged in professional development using collaborative Web (Web 20) technologies This community of practice (CoP) consisted of world language (WL) teachers using the microblogging platform, Twitter The study approached teacher learning from a sociocultural perspective Its central questions were as follows: What are the characteristics of this CoP of WL educators on Twitter? How do those characteristics relate to or reflect teacher learning? With a qualitative, netnographic approach, data sources included over a year of participant observation, nine interviews with community members, and numerous online documents from blogs, wikis, and other sources Findings demonstrated how the domain, community, and practice characteristics of this online CoP could also be linked to sustained and significant teacher learning The study concludes with considerations for the future of similar online communities