Adam Bermingham

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Microblogs as a new textual domain offer a unique proposition for sentiment analysis. Their short document length suggests any sentiment they contain is compact and explicit. However, this short length coupled with their noisy nature can pose difficulties for standard machine learning document representations. In this work we examine the hypothesis that it(More)
The body of content available on Twitter undoubtedly contains a diverse range of political insight and commentary. But, to what extent is this representative of an electorate? Can we model political sentiment effectively enough to capture the voting intentions of a nation during an election capaign? We use the recent Irish General Election as a case study(More)
While most work in sentiment analysis in the financial domain has focused on the use of content from traditional finance news, in this work we concentrate on more subjective sources of information, blogs. We aim to automatically determine the sentiment of financial bloggers towards companies and their stocks. To do this we develop a corpus of financial(More)
The increased online presence of jihadists has raised the possibility of individuals being radicalised via the Internet. To date, the study of violent radicalisation has focused on dedicated jihadist websites and forums. This may not be the ideal starting point for such research, as participants in these venues may be described as "already made-up minds".(More)
In this paper we describe our work in the area of topicbased sentiment analysis in the domain of financial blogs. We explore the use of paragraph-level and document-level annotations, examining how additional information from paragraph-level annotations can be used to increase the accuracy of document-level sentiment classification. We acknowledge the(More)
This paper presents and evaluates a novel approach for automatically recommending multimedia content for use in group reminiscence therapy for people with Alzheimer's and other dementias. In recent years recommender systems have seen popularity in providing a personalised experience in information discovery tasks. This personalisation approach is naturally(More)
The recent prominence of the real-time web is proving both challenging and disruptive for information retrieval and web data mining research. User-generated content on the real-time web is perhaps best epitomised by content on microblogging platforms, such as Twitter. Given the substantial quantity of microblog posts that may be relevant to a user’s query(More)