Emotions in Twitter communication and stock prices of firms: the impact of Covid-19 pandemic

Abstract

In this paper, we explored two key aspects of organization theory-organizational communication in the face of crisis and the influence of emotions expressed in social media communication and their impact on stock prices of firms. We extracted emotional content from 189,303 tweets and collected financial data for six quarters for 105 companies listed on the New York Stock Exchange from the Fortune 1000 list of companies. We operationalized a set of metrics to measure emotion in organizational tweets. Our analysis showed that the operationalized metrics to measure emotion expressed in organizational tweets were significant predictors of stock prices of firms. Further analysis showed a moderation effect of the crisis on the association between emotion expressed in organizational tweets and stock prices in the presence of control variables. The study provides a detailed analysis of constituent positive (happiness) and negative (anger, fear, and sadness) emotions in organizational tweets and their association with stock prices of firms. Practitioners and regulators may use the analysis and the metrics to assess organizational communication and better leverage Twitter for crisis response. This paper showcases organizational crisis response of Twitter and its financial impact.

Engagement of the e-commerce industry in the US, according to Twitter in the period of the COVID-19 pandemic

“…Specifically in the initial period of the pandemic, according to the results of [ 96 ] indicates that stock market returns decrease as the number of confirmed cases in a country increases, however, is contrasted with the results obtained in the present study of the E-Commerce industry, due to the fact that most e-commerce companies, except Macy's, increased their returns on their stock prices as the health crisis grew. Continuing with the results obtained in this investigation, it was shown that the level of Engagement on Twitter does not influence the price of the shares, and despite the fact that this has been the result of the study, it can be a precedent but not necessarily It should always be this way, since in the research of [ 97 ] that corresponds to the analysis of emotion scores of company tweets, these have a significant impact on the price of their shares, as so too is the increase in Twitter posts, which according to the above study will improve a company's stock price performance. This is why companies carry out initiatives through social networks to involve the public, considered beneficial for companies, since they allow them to function as promotional or marketing strategies and thus easily cover a large number of potential customers through information dissemination [ 98 ].…”

Sentiment Analysis and Emotion Detection on Cryptocurrency Related Tweets Using Ensemble LSTM-GRU Model

“…Text2Emotion is a Python package created to identify appropriate emotions embedded in the text data [27]. Humans use emotions in the appropriate context while communicating and the words used to represent those emotions are properly aligned.…”

Analyzing the attitude of Indian citizens during the second wave of COVID-19: A text analytics study

“…Since sentiment analysis merely report polarity of text content whether positive, negative, or neutral, few prior studies analyzed emotions expressed by the authors in the text content [ 3 , 11 ]. Hence, this study also examined the emotions expressed in each tweet using text2emotion Python Library.…”