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Publication
Applications of opinion mining to data journalism
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Authors
Abstract(s)
Nowadays social media play a central role in every day life. A huge volume
of user-generated data spins around online social networks, such as Twitter, having
an extraordinary impact on the media industry and on the users’ everyday life. More
and more users and people use social networks from their computers and
smartphones to share their emotions and opinions about the facts happening in the
world. Natural language processing and, in particular, sentiment analysis are key
technologies to make sense out of the data about news that circulates in the online
social networks. The application of opinion mining to news-oriented user-generated
contents, such as news-linking tweets, can provide novel views on the news
audience behaviour and help to interpret the evolution of sentiments. Applying this
capability in the social news-sphere permits (i) to measure the impact of news onto
readers and (ii) to gather elements that contain stories.
From a broad perspective, the main aim of this research is to face this
challenge, that is, to explore how opinion mining (or sentiment analysis) can be
adopted into the field of digital media and data-driven journalism.
Description
Dissertação de mest., Processamento de Linguagem Natural e Indústrias da Língua, Faculdade de Ciências Humanas e Sociais, Univ. do Algarve, 2013
Keywords
Meios de comunicação Media Jornalismo Processamento de linguagem natural Sociedade da informação