When the Going Gets Tough, The Tweets Get Going! An Exploratory Analysis of Tweets Sentiments in the Stock Market

Abstract

Information artifacts in social media can have significant impact on domains and subject matter opinions. Asset prices, stock prices and volumes, and metrics are influenced by turbulence in their information ecosystems. Analyses of digital information networks and social media information events have shown information artifacts to affect stock performance without consistent correlation to fundamentals. Thus it becomes important to dispel ambiguity and gain insights into how the sentiments associated with information artifacts in Twitter (due to its extensive usage in relevant signaling), are associated with equity movements. Using an exploratory analysis to study tweet sentiment, we link stock price variations, and explore associated metrics. Our tweets analytics deploying textual analytics, identifies forms in tweet behavior and sentiment shifts.

Application of sentence-level text analysis: The role of emotion in an experimental learning intervention

“…Although sentimentr has not been used in mainstream psychology, it has been applied to many areas of research involving the study of emotion, such as public opinions in business and management (Ikoro, Sharmina, Malik, & Batista-Navarro, 2018;Sinha, Choudhury, & Agrawal, 2014), political science (Sanders, 2018) and even predicting stock trend from sentiments reflected in the market and social media (J. Chen et al, 2015;Samuel & Kretinin, 2018).…”

The pandemic semesters: Examining public opinion regarding online learning amidst COVID‐19

“…In recent times, social media platforms have been one of the quickest means for people to express their thoughts, emotions, and activities about immediate social phenomena such as education, finances, health, natural disasters, social trends, and so on (Samuel et al, 2020). Consequently, researchers have been using data generated from social media platforms such as Twitter to identify opinions and emotions on a number of public and social related issues (Shu et al, 2017;Kretinin et al, 2018).…”

“…Twitter users mostly utilize the platform to share their thoughts, opinions and disseminate information. The wealth of shared views on this platform has encouraged many researchers to gather data from the platform to examine sentiments on numerous social issues (Blank, 2017;Chae, 2015;Kretinin et al, 2018;Peoples et al, 2016;Sinnenberg et al, 2017). To leverage the significance of data on the Twitter platform, the researchers scrapped tweets from the Twitter platform using Tweepy and Twitterscraper library along with Twitter developers API (Twitter, 2020) in Python language.…”

Application of sentence-level text analysis: The role of emotion in an experimental learning intervention

“…Although sentimentr has not been used in mainstream psychology, it has been applied to many areas of research involving the study of emotion, such as public opinion in business and management (Ikoro, Sharmina, Malik, & Batista-Navarro, 2018;Sinha, Choudhury, & Agrawal, 2014), political science (Sanders, 2018) and even predicting stock trend from sentiments reflected in the market and social media (J. Chen et al, 2015;Samuel & Kretinin, 2018).…”