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.

Connecting Social Media to E-Commerce: Cold-Start Product Recommendation Using Microblogging Information

Abstract: In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper, we propose a novel solution for cross-site cold-start product recommendation , which aims to recommend products from e-commerce websites to users at social networking sites in “cold-start” situations, a problem which has rarely been explored before. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation. We propose to use the linked users across social networking sites and e-commerce websites (users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users’ social networking features to another feature representation for product recommendation. In specific, we propose learning both users’ and products’ feature representations (called user embeddings and product embeddings, respectively) from data collected from e-commerce websites using recurrent neural networks and then apply a modified gradient boosting trees method to transform users’ social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can leverage the learnt user embeddings for cold-start product recommendation. Experimental results on a large dataset constructed from the largest Chinese microblogging service Sina Weibo and the largest Chinese B2C e-commerce website JingDong have shown the effectiveness of our proposed framework.

TopicSketch: Real-Time Bursty Topic Detection from Twitter

Abstract: Twitter has become one of the largest microblogging platforms for users around the world to share anything happening around them with friends and beyond. A bursty topic in Twitter is one that triggers a surge of relevant tweets within a short period of time, which often reflects important events of mass interest. How to leverage Twitter for early detection of bursty topics has therefore become an important research problem with immense practical value. Despite the wealth of research work on topic modelling and analysis in Twitter, it remains a challenge to detect bursty topics in real-time. As existing methods can hardly scale to handle the task with the tweet stream in real-time, we propose in this paper $\sf {TopicSketch}$ , a sketch-based topic model together with a set of techniques to achieve real-time detection. We evaluate our solution on a tweet stream with over 30 million tweets. Our experiment results show both efficiency and effectiveness of our approach. Especially it is also demonstrated that $\sf {TopicSketch}$ on a single machine can potentially handle hundreds of millions tweets per day, which is on the same scale of the total number of daily tweets in Twitter, and present bursty events in finer-granularity.

What Trends in Chinese Social Media

Abstract: There has been a tremendous rise in the growth of online social networks all over the world in recent times. While some networks like Twitter and Facebook have been well documented, the popular Chinese microblogging social network Sina Weibo has not been studied. In this work, we examine the key topics that trend on Sina Weibo and contrast them with our observations on Twitter. We nd that there is a vast dierence in the content shared in China, when compared to a global social network such as Twitter. In China, the trends are created almost entirely due to retweets of media content such as jokes, images and videos, whereas on Twitter, the trends tend to have more to do with current global events and news stories.

A diffusion mechanism for social advertising over microblogs

Abstract: Social media have increasingly become popular platforms for information dissemination. Recently, companies have attempted to take advantage of social advertising to deliver their advertisements to appropriate customers. The success of message propagation in social media depends greatly on the content relevance and the closeness of social relationships. In this paper, considering the factors of user preference, network influence, and propagation capability, we propose a diffusion mechanism to deliver advertising information over microblogging media. Our experimental results show that the proposed model could provide advertisers with suitable targets for diffusing advertisements continuously and thus efficiently enhance advertising effectiveness.

The Emerging Viewertariat and BBC Question Time: Television Debate and Real-Time Commenting Online

Abstract: This paper advances the study of microblogging and political events by investigating how one high-profile broadcast acted as a stimulus to real-time commentary from viewers using Twitter. Our case study is a controversial, high-ratings episode of BBC Question Time, the weekly British political debate show, in October 2009, in which Nick Griffin, leader of the far-right British National Party, appeared as a panelist. The "viewertariat" emerging around such a political event affords the opportunity to explore interaction across media formats. We examine both the structural elements of engagement online and the expressions of collective identity expressed in tweets. Although many concerns noted in previous studies of online political engagement remain (inequality in the propensity to comment, coarseness of tone), we find certain notable characteristics in the sample, especially a direct link between the quantity of tweets and events on the screen, an ability to preempt the arguments offered by panelists, and ways in which viewertariat members add new content to the discussion. Furthermore, Twitter users commenting online express a range of overlapping identities. These complexities challenge broadcasting and political institutions seeking to integrate new, more organic models of engagement.