Keyword-Based Sentiment Mining using Twitter
نویسندگان
چکیده
منابع مشابه
Keyword-Based Sentiment Mining using Twitter
Today’s connected society is characterized by the way people share information and by how such information affects the community as a whole. This is particular relevant when such information reflects the opinion of individuals about other individuals, companies, products, specific product features, etc. Arguably, Twitter is one of the most popular platforms for publishing opinions and other inf...
متن کاملLocalized twitter opinion mining using sentiment analysis
Background Sentiment analysis technique is an effective means of discovering public opinions. Various companies often use online or paper based surveys to collect customer comments. Due to the emergence of social networking sites and applications, people tend to comment on their facebook or tweet profile. Therefore the paper based approach is not an efficient approach. Only a very small custome...
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Today, social networks are fast and dynamic communication intermediaries that are a vital business tool. This study aims at examining the views of those involved with Facebook stocks so that we can summarize their views to predict the general behavior of this stock and collectively consider possible Facebook stock price movements, and create a more accurate pattern compared to previous patterns...
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In this paper, we describe our system which participated in the SemEval 2010 task of disambiguating sentiment ambiguous adjectives for Chinese. Our system uses text messages from Twitter, a popular microblogging platform, for building a dataset of emotional texts. Using the built dataset, the system classifies the meaning of adjectives into positive or negative sentiment polarity according to t...
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This paper outlines a new language-independent model for sentiment analysis of short, social-network statuses. We demonstrate this on data from Twitter, modelling happy vs sad sentiment, and show that in some circumstances this outperforms similar Naive Bayes models by more than 10%. We also propose an extension to allow the modelling of different sentiment distributions in different geographic...
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ژورنال
عنوان ژورنال: International Journal of Ambient Computing and Intelligence
سال: 2013
ISSN: 1941-6237,1941-6245
DOI: 10.4018/jaci.2013040104