PPT-Finding Correlations Between Geographical Twitter Sentiment and Stock Prices

Undergraduate Researchers Juweek Adolphe Ressi Miranda Graduate Student Mentor Zhaoyu Li Faculty Advisor Dr Yi Shang. Abhijit. Mishra. 1. , . Aditya. Joshi. 1,2,3. , . Pushpak. Bhattacharyya. 1. 1 . IIT Bombay, India . 2 . Monash. University, Australia. 3. IITB-Monash Research Academy. At 5th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, ACL 2014, Baltimore . 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=&. 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=&. For EECSE 6898-From Data to Solutions class. Presented by-Tulika Bhatt(tb2658). What do stock prices depend on?. Fundamental Factors. -Earning base. -Valuation Multiple. Technical Factors. -Inflation, Economic Strength of Market and Peers, Substitutes, Incidental Transactions, Trends, Demographics, Liquidity. Lesson 14. Discovering the Law of Demand. Amount. you pay for one cup of Stomping Grounds Coffee. 1. 2. 3. 4. Total. $10. $5. $4. $3. $2. $1. $0 (free. coupons). Lesson 14 – How are Stock Prices Determined?. 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. For EECSE 6898-From Data to Solutions class. Presented by-Tulika Bhatt(tb2658). What do stock prices depend on?. Fundamental Factors. -Earning base. -Valuation Multiple. Technical Factors. -Inflation, Economic Strength of Market and Peers, Substitutes, Incidental Transactions, Trends, Demographics, Liquidity. 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. Authors: Joseph Watts, Nick Anderson, Joseph . Mehr. , Connor . Asbill. Client: Saurabh Chakravarty. Professor: Edward Fox. Virginia Tech - Blacksburg, VA . 2406. 1. . CS . 4624. :. Multimedia. , . Slides from Bing Liu and Ronan Feldman. Introduction. Two main types of textual information. . Facts and Opinions. Note: factual statements can imply opinions too.. Most current text information processing methods (e.g., web search, text mining) work with factual information.. 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. and opinion mining. ‹#›. Bettina Berendt. Department of Computer Science. KU Leuven, Belgium. http://people.cs.kuleuven.be/~bettina.berendt/. Vienna Summer School on Digital Humanities. July 7. th. 1 ACT, 1999 ______________ ARRANGEMENT OF SECTIONS ___________ CHAPTER I P RELIMINARY S ECTIONS 1. Short ti tle, extent and commencement. 2. Definitions and interpretation. CHAPTER II T HE REGISTER A Maureen Cowhey, Seung Jung Lee. Thomas Popeck Spiller, and Cindy M. Vojtech . September 29, 2022. Disclaimer: The views expressed herein are those of the authors, and do not necessarily represent the views of the Federal Reserve Board or its staff..