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Recently, with the increasing of users and activities in social network service, an image sentiment analysis has been an important keyword for psychological study and commercial marketing. To recognize accurately user's sentiments of the image, it is essential to identify discriminative visual features and then
The growing popularity of social network services has led to many studies of various phenomena in this area. However, most of this research has been conducted using English language data, and relatively little has considered Korean. In this paper, we demonstrate a systematic analysis framework using Korean Twitter
favorite restaurant. The sentiment analysis for restaurant rating system rates the restaurant depending upon the reviews given by the users. The system breaks user comments to check for sentiment keywords. Once the keywords are found, it associates the comment with a sentiment rank. Sentiment analysis can also be extended
news sites discussing extremism and finally sites with no discussion of extremism. Then parts of speech tagging was used to find the most frequent keywords in these pages. Utilizing sentiment software in conjunction with classification software a decision tree that could effectively discern which class a particular page
overall life time. The "bag-of-words" model is used to represent the content of an article as a vector of features, which are uni-, bi-, or tri-gram keywords. The thesaurus approach is applied to group words with similar meanings to a set of root words to reduce the size of the feature space. Normalized TF-IDF
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.