Positivity and Negativity Attributes of Users in Twitter
Sapana Mahaveer patil
Social media is a platform where people create content, share their opinions, vision and concepts. Examples include Facebook, MySpace, Digg, Twitter and JISC list serves on the academic side, because of its simplicity, speed and reach, social media is rapidly changing the public chat in society and setting trends and agendas in case that limits from the environment and politics to technology and the entertainment industry. Since social media can also be presumed as a form of mutual wisdom, it can be used to predict real-world outcomes. “The Wisdom of Crowds” is about the gathering of info in groups, emerging in decisions that are often better than could have been made by any single member of the group. The popular saying on social media goes as follows: “We use Facebook to record the protests, Twitter to coordinate, and YouTube to tell the world.” Twitter is the place where we all gather to express precisely the point of view and feelings about specific topics. Opinions reveal beliefs about specific matter commonly considered to be subjective. Twitter has millions of users that spread millions of personal posts on a daily basis. And this gives us the opportunity to study social human subjectivity. Manual classification of thousands of posts for opinion mining task is unfeasible for a human being.
Mood, emotions, twitter, facebook, social network graph
 M. Cataldi, L. Di Caro, and C. Schifanella. Emerging topic detection on twitter based on temporal and social terms evaluation. 2010.
 B. J. Jansen, M. Zhang, K. Sobel, and A. Chowdury. Twitter power: Tweets as electronic word of mouth. Journal of the American Society for Information Science and Technology, 60(11):2169–2188, 2009.
U. Waltinger. Polarity reinforcement: Sentiment polarity identification by means of social semantics. 2009.
 S. Asur and B.A. Huberman. Predicting the future with social media,2010.
 Mining Social Media Data for Understanding Students’ Learning Experiences Xin Chen, Student Member, IEEE, Mihaela Vorvoreanu, and Krishna Madhavan.
 Predicting User-Topic Opinions in Twitter with Social and Topical Context Fuji Ren, Senior Member, IEEE, and Ye Wu ,Ieee transactions on affective computing, vol. 4, no. 4, october-december 201
[Sapana Mahaveer patil (2015), Positivity and Negativity Attributes of Users in Twitter, International Journal of Innovative Research in Computer Science & Technology (IJIRCST), Vol-3, Issue-6, Page No-19-24], (ISSN 2347 - 5552). www.ijircst.org
Sapana Mahaveer patil
Information Technology, Savitribai Phule university Pune,Sidhhant College Of Engineering , Pune, India, Mobile No. +918793595443, (e-mail: firstname.lastname@example.org/ email@example.com).