Unveiling the Patterns of Video Tweeting: A Sina Weibo-Based Measurement Study

Guo, Zhida; Huang, Jian; He, Junjia; Hei, Xiaojun; Wu, Di

doi:10.1007/978-3-642-36516-4_17

Cited by 19 publications

(12 citation statements)

References 5 publications

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“…Once being launched, crowdfunding projects have a potential to be spread to other websites (e.g., Twitter, Weibo, WeChat) and viewed by potential funders [34]. Apparently, crowdfunding project with great number of retweets, comments, and likes are popular.…”

Section: Activating Internal Reactions: Stimulus Of Environmental Cuesmentioning

confidence: 99%

Donation Behavior in Online Micro Charities: An Investigation of Charitable Crowdfunding Projects

Liu¹,

Suh²,

Wagner³

2017

Proceedings of the Annual Hawaii International Conference on System Sciences

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Section: Activating Internal Reactions: Stimulus Of Environmental Cuesmentioning

confidence: 99%

Donation Behavior in Online Micro Charities: An Investigation of Charitable Crowdfunding Projects

Liu¹,

Suh²,

Wagner³

2017

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…For example, many OSN applications, such as Facebook, Weibo, allow users to "check-in" and explicitly show their locations (Guo et al, 2013;Nazir et al, 2008;Liao et al, 2015); some other applications have implicitly recorded users' georelated information such as GPS coordinates, IP address Zheng et al, 2010). Existing research has shown the feasibility of using the OSN data to predict users' offline locations as well their mobility patterns (Cho et al, 2011;Li et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Modeling geo-homopholy in online social networks for population distribution projection

Zhang

Bian

et al. 2017

IJCS

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.*Related content and download information correct at time of download. Purpose -Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people's trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN) apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geohomophily in the online social networks.Design/methodology/approach -In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions. Findings -By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time.Originality/value -This paper tries to project population distribution by modeling geo-homophily in OSNs.

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“…http://www.washingtonpost.com/blogs/worldviews/wp/2013/03/08/how-china-censors-100-milliontweets-per-day/ 6) The comment feature has been in Sina Weibo since its inception 7) Twitter supports the function of displaying the full conversations in Aug., 2013. https://blog.twitter.com/2013/keep-up-with-conversations-on-twitter 8) Each API request returns 200 public tweets 9) When users A and B follow each other in a bidirectional social link, we call them friends comprehensive sample of Sina Weibo social network to date. More importantly, while the prior efforts focused on the social graph and tweet content [2,[7][8][9][10], our datasets contain all reposts and comments for 61.5 million tweets.…”

Section: Crawling Reposts and Commentsmentioning

confidence: 99%

“…For each user, we define a commentor as any other user who 10) This covers more than 99% of the tweets, because less than 1% of the tweets have more than 30 reposts or 50 comments has posted at least one comment on his tweets. We now study the composition of commentors with three key questions: 1) how many commentors does a user have, 2) what portion of these commentors are the user's friends and 3) what are the relationships among the commentors?…”

Section: Composition Of Commentorsmentioning

confidence: 99%

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The power of comments: fostering social interactions in microblog networks

Wang

Chen

Wang

et al. 2016

Front. Comput. Sci.

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Today's ubiquitous online social networks serve multiple purposes, including social communication (Facebook, Renren), and news dissemination (Twitter). But how does a social network's design define its functionality? Answering this would need social network providers to take a proactive role in defining and guiding user behavior.In this paper, we first take a step to answer this question with a data-driven approach, through measurement and analysis of the Sina Weibo microblogging service. Often compared to Twitter because of its format, Weibo is interesting for our analysis because it serves as a social communication tool and a platform for news dissemination, too. While similar to Twitter in functionality, Weibo provides a distinguishing feature, comments, allowing users to form threaded conversations around a single tweet. Our study focuses on this feature, and how it contributes to interactions and improves social engagement. We use analysis of comment interactions to uncover their role in social interactivity, and use comment graphs to demonstrate the structure of Weibo users interactions. Finally, we present a case study that shows the impact of comments in malicious user detection, a key application on microblogging systems. That is, using properties of comments significantly improves the accuracy in both modeling

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Unveiling the Patterns of Video Tweeting: A Sina Weibo-Based Measurement Study

Cited by 19 publications

References 5 publications

Donation Behavior in Online Micro Charities: An Investigation of Charitable Crowdfunding Projects

Donation Behavior in Online Micro Charities: An Investigation of Charitable Crowdfunding Projects

Modeling geo-homopholy in online social networks for population distribution projection

The power of comments: fostering social interactions in microblog networks

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