Related papers: Event Outcome Prediction using Sentiment Analysis …

The rise in popularity and ubiquity of Twitter has made sentiment analysis of tweets an important and well-covered area of research. However, the 140 character limit imposed on tweets makes it hard to use standard linguistic methods for…

Social Media usage has increased to an all-time high level in today's digital world. The majority of the population uses social media tools (like Twitter, Facebook, YouTube, etc.) to share their thoughts and experiences with the community.…

With public information becoming widely accessible and shared on today's web, greater insights are possible into crowd actions by citizens and non-state actors such as large protests and cyber activism. We present efforts to predict the…

Twitter updates now represent an enormous stream of information originating from a wide variety of formal and informal sources, much of which is relevant to real-world events. In this paper we adapt existing bio-surveillance algorithms to…

State of the art benchmarks for Twitter Sentiment Analysis do not consider the fact that for more than half of the tweets from the public stream a distinct sentiment cannot be chosen. This paper provides a new perspective on Twitter…

A large number of studies on social media compare the behaviour of users from different political parties. As a basic step, they employ a predictive model for inferring their political affiliation. The accuracy of this model can change the…

A vast amount of textual web streams is influenced by events or phenomena emerging in the real world. The social web forms an excellent modern paradigm, where unstructured user generated content is published on a regular basis and in most…

Opinion evolution and judgment revision are mediated through social influence. Based on a large crowdsourced in vitro experiment (n=861), it is shown how a consensus model can be used to predict opinion evolution in online collective…

Social media tend to be rife with rumours while new reports are released piecemeal during breaking news. Interestingly, one can mine multiple reactions expressed by social media users in those situations, exploring their stance towards…

Predicting popularity, or the total volume of information outbreaks, is an important subproblem for understanding collective behavior in networks. Each of the two main types of recent approaches to the problem, feature-driven and generative…

Word embeddings or distributed representations of words are being used in various applications like machine translation, sentiment analysis, topic identification etc. Quality of word embeddings and performance of their applications depends…

Twitter is one of the most popular microblogging services in the world. The great amount of information within Twitter makes it an important information channel for people to learn and share news. Twitter hashtag is an popular feature that…

We expect that democracy enables us to utilize collective intelligence such that our collective decisions build and enhance social welfare, and such that we accept their distributive and normative consequences. Collective decisions are…

Analysis of information retrieved from microblogging services such as Twitter can provide valuable insight into public sentiment in a geographic region. This insight can be enriched by visualising information in its geographic context. Two…

Twitter, a microblogging service, is todays most popular platform for communication in the form of short text messages, called Tweets. Users use Twitter to publish their content either for expressing concerns on information news or views on…

This paper describes the analysis of quantitative characteristics of frequent sets and association rules in the posts of Twitter microblogs, related to the discussion of "end of the world", which was allegedly predicted on December 21, 2012…

An important aspect of urban planning is understanding crowd levels at various locations, which typically require the use of physical sensors. Such sensors are potentially costly and time consuming to implement on a large scale. To address…

In microblogging, hashtags are used to be topical markers, and they are adopted by users that contribute similar content or express a related idea. However, hashtags are created in a free style and there is no domain category information…

Social media platforms contain a great wealth of information which provides opportunities for us to explore hidden patterns or unknown correlations, and understand people's satisfaction with what they are discussing. As one showcase, in…

With the pervasiveness of online media data as a source of information verifying the validity of this information is becoming even more important yet quite challenging. Rumors spread a large quantity of misinformation on microblogs. In this…