Sentiment Computing for Visual Emotion Generation on Social Media using Text Mining

International Journal of Computer Trends and Technology (IJCTT)          
© 2018 by IJCTT Journal
Volume-66 Number-1
Year of Publication : 2018
Authors : Nayana More, Deepali Jadhav


MLA Style: Nayana More, Deepali Jadhav "Sentiment Computing for Visual Emotion Generation on Social Media using Text Mining" International Journal of Engineering Trends and Technology 66.1 (2018): 1-7.

APA Style: Nayana More, Deepali Jadhav (2018). Sentiment Computing for Visual Emotion Generation on Social Media using Text Mining. International Journal of Engineering Trends and Technology, 66(1), 1-7.

The fast increase of the World Wide Web has helped increased online communication and opened up newer streets for the general public to post their opinions online. This has led to a generation of large amounts of online content rich in user opinions, sentiments, emotions, and evaluations. We need computational approaches to successfully analyse this online content, recognize and aggregate relevant information, and draw useful conclusions. Much of the current work in this direction has typically focused on recognizing the polarity of sentiment (positive/negative). In this writing, we have suggested a system that recognizes the emotion from the text of Social networking websites by using a modified approach that uses affective word based and sentence context level emotion classification method. Also to adequately express the emotion of a user we have developed a visual image generation approach that generates images according to emotion in text.

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Emotion, Sentiment, Classification, Social Networking, Recognizing, Accuracy, Extraction, Tagging, Detection, Pre-processing;