Applying sentiment analytics to examine social media crises: a case study of United Airline's crisis in 2017

Abstract

PurposeIn recent years, social media crises occurred more and more often, which negatively affect the reputations of individuals, businesses and communities. During each crisis, numerous users either participated in online discussion or widely spread crisis-related information to their friends and followers on social media. By applying sentiment analysis to study a social media crisis of airline carriers, the purpose of this research is to help companies take measure against social media crises.Design/methodology/approachThis study used sentiment analytics to examine a social media crisis related to airline carriers. The arousal, valence, negative, positive and eight emotional sentiments were applied to analyze social media data collected from Twitter.FindingsThis research study found that social media sentiment analysis is useful to monitor public reaction after a social media crisis arises. The sentiment results are able to reflect the development of social media crises quite well. Proper and timely response strategies to a crisis can mitigate the crisis through effective communication with the customers and the public.Originality/valueThis study used the Affective Norms of English Words (ANEW) dictionary to classify the words in social media data and assigned the words with two elements to measure the emotions: valence and arousal. The intensity of the sentiment determines the public reaction to a social media crisis. An opinion-oriented information system is proposed as a solution for resolving a social media crisis in the paper.

Sentiment analysis of Indian Tweets about Covid-19 vaccines

“…Infectious disease outbreaks and other health problems were widely discussed and shared on social media [ 33 , 34 ]. Sentiment analysis of social media data is emerging as an important research field and is in use at different spheres, namely, e-sports [ 35 , 36 ], sports [ 37 – 41 ] healthcare [ 42 – 44 ] and even geopolitical conflicts and crises [ 45 – 50 ]. Since the Covid-19 outbreak, a number of studies throughout the world have utilised Twitter data to assess the public opinion [ 21 , 28 , 51 – 57 ], main discussion themes [ 58 – 61 ] and misinformation [ 62 – 64 ] about the Covid-19 vaccine.…”

Examining Crisis Communication Using Semantic Network and Sentiment Analysis: A Case Study on NetEase Games

“…Based on Twitter, Kaur et al (2021) explored the impact of crisis communication strategies of Indian leaders in public health events after the outbreak of COVID-19 on the public's emotions, which can be divided into 10 types, including anger, expectation, disgust, and fear. Similarly, based on Twitter, Tian et al (2021) divided sentiments into eight categories, including arousal and valence, and examined the crisis of United Airlines' in 2017. The authors found that social media sentiment analysis can help identify public responses and help enterprises adopt appropriate communication strategies.…”

Unpacking the Evolution of a Paracrisis: The Case of #DeleteUber

“…For paracrises constructed by multiple, sometime conflicting voices, effective responses cannot be developed without identifying and understanding influential public voices. Over the past few years, scholars and practitioners have explored various tools to examine publics' social media communication during crises, such as automated content analysis (e.g., Van Der Meer 2016) and sentiment analysis (e.g., Tian and Wang 2021). While these tools excel in identifying topics and emotions from large amounts of texts, they are limited in generating insights for prioritizing or predicting social media voices during paracrises.…”