PPT-Sentiment Analysis & Opinion Mining

Lecture Two March 3 2011 Aditya M Joshi M Tech3 CSE IIT Bombay adityajcseiitbacin Sentiment analysis SA Task of tagging text with orientation of opinion This is a good movie. sentiment analysis, and beyond. Bettina Berendt. Department . o. f Computer Science. KU Leuven, Belgium. http://people.cs.kuleuven.be/~bettina.berendt. /. Summer School . Foundations and Applications of Social Network Analysis & Mining. , OPINIONS, EMOTIONS. Heng. . Ji. jih@rpi.edu. October 22, 2014. Acknowledgement: Some slides from Jan . Wiebe. and . Kavita. . Ganesan. . 2. OUTLINE. Emotion Detection. Subjectivity Overview. Sentiment Analysis. Heng. . Ji. jih@rpi.edu. October . 28, 2015. Acknowledgement: Some slides from Jan . Wiebe. and . Kavita. . Ganesan. . Emotion Examples. A Happy Song? . A Sad Song. ?. http. ://y.qq.com/webplayer/p.html?songList=%5B%5D&type=1&vip=-1&userName=&ipad=0&from=0&singerid=0&encodedUIN=&. BY,. SOWMYA KAMATH,. ANUSHA BAGAL KOTHKAR,. KUMARI POORNIMA,. SHIVAM PANDEY. AND. ASHESH KHANDELWAL. Introduction. Approaches to Sentiment Analysis. Sentiment Analysis Applications. Current development in Sentiment Analysis. Heng. . Ji. jih@rpi.edu. October . 25, 2016. Acknowledgement: Some slides from Jan . Wiebe. and . Kavita. . Ganesan. . Emotion Examples. A Happy Song? . A Sad Song. ?. http. ://y.qq.com/webplayer/p.html?songList=%5B%5D&type=1&vip=-1&userName=&ipad=0&from=0&singerid=0&encodedUIN=&. Yuh. Day. 戴敏育. Assistant Professor. 專任助理教授. . Dept. of Information Management. , . Tamkang. University. 淡江大學.  . 資訊管理學系. http://mail. tku.edu.tw/. myday. /. 2016-11-01. Giacomo Righetti, dept. of Computer Science, University of Pisa, ISTI-CNR. Agenda. Part I. Introduction. Motivations . and Issues . User level informations. Topics. Part II. Discussion about topics. Giacomo Righetti, dept. of Computer Science, University of Pisa, ISTI-CNR. SENTIMENT ANALYSIS. FACTS AND OPINIONS. Two main types of textual information on the . Web: FACTS . and. OPINIONS. Current search engines search for facts (assume they are true). Facts can be expressed with topic keywords. Machine Learning with Large Datasets. Course Project . (under. . the. . guidance. . of. . P. rof. . W. illiam. W. C. ohen. ). T. eam. M. embers. : M. anuel. , S. hubham. . and. S. oumya. 1. Outline. David A. Schweidel. Goizueta. Business School. Emory University. October . 2012. What’s Trending on Social Media?. Agenda. Social Dynamics in Social Media Behavior. Why do people post a product opinion? What influences their posting behavior? (Moe and . Awais. . Athar. . &. Simone . Teufel. Sentiment Analysis of Citations. Challenges in Citation Sentiment Analysis. Negative sentiment is ‘politically dangerous’. - (. Z. iman. , . 1968). Personal biases are h. Md. . Mustafizur. . Rahman. and . Hongning. Wang. Department of Computer Science. University of Virginia, Charlottesville,. Virginia, VA 22903. 2. I especially like its . portability. (3 pounds with a . Positive or negative movie review?. unbelievably . disappointing . Full of . zany characters and richly applied satire, and some great plot . twists. this is the greatest screwball comedy ever . filmed. Positive or negative movie review?. unbelievably . disappointing . Full of . zany characters and richly applied satire, and some great plot . twists. this is the greatest screwball comedy ever . filmed.