@inproceedings{c86bb61bf7244246b83fbd40d0f33c01,
title = "Analyzing relationship: Twitter tweet frequency with the stock prices of telecom companies",
abstract = "Twitter is a widely used online social media. In this paper, we investigate whether the daily number of tweets that mention any of the telecom companies i.e. Verizon, T-Mobile, AT&T and Sprintvis-{\`a}-vis stock prices.The study focuses on correlating data sets of Twitter tweet frequency with the stock prices of telecom Companies; using Statistical Methods: Z-score and Chi-Square - Test of Independence with data visualization.Our results demonstrate the relation between daily numbers of tweets is correlated with that of stock price for Verizon and T-Mobile. Our preliminary results also demonstrate the relation of frequency of tweets with stock prices of each day. Furthermore, it appears that Twitter tweets and stock prices are independent.",
keywords = "Correlation, Stock prices, T-Mobile, Tweet frequency, Verizon",
author = "Amrita Shelar and Huang, {Ching yu}",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery.; 2018 International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2018 ; Conference date: 15-08-2018 Through 17-08-2018",
year = "2018",
month = aug,
day = "15",
doi = "10.1145/3243250.3243267",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "113--116",
booktitle = "Proceedings of 2018 International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2018",
}