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A Context-Aware Analytics for Processing Tweets and Analysing Sentiment in Realtime (Short Paper)

Abstract : Sentiment analysis has grown to become increasingly important for companies to more accurately understand customer/supplier sentiments about their processes/products and services, and predict customer churn. In particular, existing sentiment analysis aims to better understand their customer’s or supplier’s emotions which are essentially the affirmative, negative, and neutral views of users on tangible or intangible entities e.g., products or services. One of the most prevalent sources to analyse these sentiments is Twitter. Unfortunately, however, existing sentiment analysis techniques suffer from three serious shortcomings: (1) they have problems to effectively deal with streaming data as they can merely exploit (Twitter) hashtags, and (2) neglect the context of Tweets. In this paper, we present SANA: a context-aware solution for dealing with streaming (Twitter) data, analysing this data on the fly taking into account context and more comprehensive semantics of Tweets, and dynamically monitoring and visualising trends in sentiments through dashboarding and query facilities.
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Contributor : Mohammad ALSHAER Connect in order to contact the contributor
Submitted on : Thursday, November 7, 2019 - 9:49:38 AM
Last modification on : Friday, September 30, 2022 - 11:34:16 AM



Yehia Taher, Rafiqul Haque, Mohammad Alshaer, Willem Jan van den Heuvel, Mohand-Said Hacid, et al.. A Context-Aware Analytics for Processing Tweets and Analysing Sentiment in Realtime (Short Paper). OTM Conferences, 2016, Rhodes, Greece. pp.910-917, ⟨10.1007/978-3-319-48472-3_57⟩. ⟨hal-02352913⟩



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