Content-Based Tweets Clustering and Analysis
نویسندگان
چکیده
منابع مشابه
Detection of Twitter Users' Attitudes about Flu Vaccine based on the Content and Sentiment Analysis of the Sent Tweets
Introduction: The influenza vaccine is one of the controversial challenges in today's societies. Considering the importance of using the flu vaccine in preventing the spread of influenza virus, the Twitter network, as a rich source of data, provides suitable conditions for research in this field to examine the attitudes of different people about this vaccine. The results in one hand will help h...
متن کاملDetection of Twitter Users' Attitudes about Flu Vaccine based on the Content and Sentiment Analysis of the Sent Tweets
Introduction: The influenza vaccine is one of the controversial challenges in today's societies. Considering the importance of using the flu vaccine in preventing the spread of influenza virus, the Twitter network, as a rich source of data, provides suitable conditions for research in this field to examine the attitudes of different people about this vaccine. The results in one hand will help h...
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The use of mixture models for clustering and classification has burgeoned into an important subfield of multivariate analysis. These approaches have been around for a half-century or so, with significant activity in the area over the past decade. The primary focus of this paper is to review work in model-based clustering, classification, and discriminant analysis, with particular attenti...
متن کاملTopical Clustering of Tweets
In the emerging field of micro-blogging and social communication services, users post millions of short messages every day. Keeping track of all the messages posted by your friends and the conversation as a whole can become tedious or even impossible. In this paper, we presented a study on automatically clustering and classifying Twitter messages, also known as “tweets”, into different categori...
متن کاملClustering tweets usingWikipedia concepts
Two challenging issues are notable in tweet clustering. Firstly, the sparse data problem is serious since no tweet can be longer than 140 characters. Secondly, synonymy and polysemy are rather common because users intend to present a unique meaning with a great number of manners in tweets. Enlightened by the recent research which indicates Wikipedia is promising in representing text, we exploit...
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ژورنال
عنوان ژورنال: International Journal on Computer Science and Engineering
سال: 2018
ISSN: 2229-5631,0975-3397
DOI: 10.21817/ijcse/2018/v10i1/181001024