In the advancement of a better understanding of user behaviour on the Internet, clustering approaches are used as a means to group and categorise online communities. Although clustering approaches indicate similarity between ...

Mentions of politicians in news articles can reflect politician interactions on their daily activities. In this work, we present a mathematical model to represent such interactions as a graph, and we use it to predict the ...

Researchers and community managers try to measure the success of online communities using a variety of success determinants, such as member activity, turnover and interaction. Although many success determinants have been ...

Relation paths are sequences of relations with inverse that allow for complete exploration of knowledge graphs in a two-way unconstrained manner. They are powerful enough to encode complex relationships between entities ...

Recommender Systems (RS) have emerged to guide users in the task of efficiently browsing/exploring a large product space, helping users to quickly identify interesting products. However, suggestions generated with traditional ...

[no abstract available]

Microblogging (mainly represented by Twitter) is a type of social media that focuses on fast open real-time communication using short messages between users and their followers. This system is attractive due to its open ...

Social Sentiment Indices powered by X-Scores (SSIX) seeks to address the challenge of extracting relevant and valuable economic signals in a cross-lingual fashion from the vast variety of and increasingly influential social ...

Learning embeddings of entities and relations using neural architectures is an effective method of performing statistical learning on large-scale relational data, such as knowledge graphs. In this paper, we consider the ...

This paper describes the second edition of the shared task on Taxonomy Extraction Evaluation organised as part of SemEval 2016. This task aims to extract hypernym-hyponym relations between a given list of domain-specific ...