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.

Adopting Social Software to the Intranet: A Case Study on Enterprise Microblogging

Abstract: Microblogging is currently one of the most discussed topics on the World Wide Web. The success of services like Twitter raises questions about their potential for organisations. In this case study we pro- vide insights from an early adopter who implemented his own microblogging system. We aim to ex- plain what use cases in professional contexts can look like and, primarily, to suggest a more precise description of what enterprise microblogging is.

Studying the values of hard-to-reach populations: content analysis of tweets by the 21st century homeless

Abstract: This paper describes a content analysis of a corpus of 5,313 tweets from 32 individuals collected during a three-week period in March/April 2011. The corpus comprised two study groups: Group H -- Twitter users who self-identified as homeless or formerly homeless in their Twitter profiles, and Group NH -- a random, stratified sample of Twitter users who did not self-identify as homeless and who shared similar Twitter characteristics with those in Group H. The study uses the Meta-Inventory of Human Values for Informal Communication (MIHV-IC) to study value expression in tweets. Two rounds of inter-coder reliability testing demonstrated the challenges of reliably detecting human values in tweets. Analysis of categories with substantial inter-coder agreement indicated significant differences between the two groups for helpfulness and wealth. This approach provides a promising opportunity for detecting the values of hard-to-reach populations such as the 21st century homeless.

Identifying local events by using microblogs as social sensors

Abstract: Local search is increasingly attracting more demand, whereby the users are interested to find out about places or events in their local vicinity. In this paper, we propose to use the Twitter microblogging platform to detect and rank local events of interest in real-time. We present a novel event retrieval framework, where both the contents of the tweets and the volume of the microblogging activity are exploited to locate an event happening in a certain area within a city that matches the user's interests as expressed in the form of a query. In particular, the framework measures unusual microblogging activities in a certain area and uses that as an indication of the occurrence of an event which is then used by the ranking function. Since the proposed event retrieval task is a new Information Retrieval (IR) task, we devise a methodology that is inspired by the conceptually similar IR problem of video segmentation to thoroughly evaluate our approach. Our evaluation is conducted on a set of tweets collected over a period of twelve days from different areas of London, as well as two sets of local events collected within the same period using crowdsourcing and local news sources in London. In addition to new insights on the factors that influence the development of an effective event ranking model, our empirical results show the promise and effectiveness of our proposed approach in identifying and ranking local events in real-time.

Sentiment analysis of Chinese microblogging based on sentiment ontology: a case study of ‘7.23 Wenzhou Train Collision’

Abstract: Sentiment analysis of microblogging texts can facilitate both organisations’ public opinion monitoring and governments’ response strategies development. Nevertheless, most of the existing analysis methods are conducted on Twitter, lacking of sentiment analysis of Chinese microblogging Weibo, and they generally rely on a large number of manually annotated training or machine learning to perform sentiment classification, yielding with difficulties in application. This paper addresses these problems and employs a sentiment ontology model to examine sentiment analysis of Chinese microblogging. We conduct a sentiment analysis of all public microblogging posts about ‘7.23 Wenzhou Train Collision’ broadcasted by Sina microblogging users between 23 July and 1 August 2011. For every day in this time period, we first extract eight dimensions of sentiment expect, joy, love, surprise, anxiety, sorrow, angry, and hate, and then build fuzzy sentiment ontology based on HowNet and semantic similarity for sentiment analysis; we also establish computing methods of influence and sentiment of microblogging texts; and we finally explore the change of public sentiment after ‘7.23 Wenzhou Train Collision’. The results show that the established sentiment analysis method has excellent application, and the change of different emotional values can reflect the success or failure of guiding the public opinion by the government.

Inferring user interests in microblogging social networks: a survey

Abstract: With the growing popularity of microblogging services such as Twitter in recent years, an increasing number of users are using these services in their daily lives. The huge volume of information generated by users raises new opportunities in various applications and areas. Inferring user interests plays a significant role in providing personalized recommendations on microblogging services, and also on third-party applications providing social logins via these services, especially in cold-start situations. In this survey, we review user modeling strategies with respect to inferring user interests from previous studies. To this end, we focus on four dimensions of inferring user interest profiles: (1) data collection, (2) representation of user interest profiles, (3) construction and enhancement of user interest profiles, and (4) the evaluation of the constructed profiles. Through this survey, we aim to provide an overview of state-of-the-art user modeling strategies for inferring user interest profiles on microblogging social networks with respect to the four dimensions. For each dimension, we review and summarize previous studies based on specified criteria. Finally, we discuss some challenges and opportunities for future work in this research domain.