scholarly journals Explainable Sentiment Analysis Application for Social Media Crisis Management in Retail

2020 ◽  
Author(s):  
Douglas Cirqueira ◽  
Fernando Almeida ◽  
Gültekin Cakir ◽  
Antonio Jacob ◽  
Fabio Lobato ◽  
...  
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Crisis Management ◽  
Analysis Application

When Consumers' Complaints Fall Into Public Domain

2020 ◽  
pp. 124-137
Author(s):  
Daniela Langaro ◽  
Sandra Maria Correia Loureiro ◽  
André Soares
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Crisis Management ◽  
Service Recovery ◽  
Public Domain ◽  
Hybrid Form ◽  
Response Strategies ◽  
Customer Care ◽  
Recovery Strategies

Despite previous studies having revealed that the content created by users in social media is predominantly positive, recent studies have challenged this understanding revealing by means of sentiment analysis the predominance of negative and neutral brand related content. The current chapter focuses on the new hybrid form of negative e-WOM in which individual´s complaints are directed at firms, which were originally limited to the domain of offline customer care teams. Thus, previous studies are reviewed from the area of crisis management and service recovery strategies with the intent to offer a relevant scope of theoretical propositions that may be considered by managers and researchers while preparing response strategies to deal with this new hybrid form of negative e-WOM. In total, eight theoretical propositions are presented and organized in three groups of guidelines associated to responses´ format, content, and context with fait-holders and hate-holders being considered as part of the negative e-WOM rhetoric.

scholarly journals Popularity of University based on Sentiment Analysis in Social Network Media

2019 ◽  
Vol 8 (3S) ◽  
pp. 25-30
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Public Image ◽  
University Of Oxford ◽  
Princeton University ◽  
Public Sentiment ◽  
The Social ◽  
Network Media ◽  
Analysis Application ◽  
Event Based

Since the emergence of the social media, many studies are conducted on social media to gain information on social media users. Among these studies are sentiment analysis which is an analysis of user sentiments and emotions towards an object, term, or event based on what they post. Sentiment analysis are often conducted on sites like Facebook and Twitter because of their huge number of users and popularity. This paper aims to create a GUI-based sentiment analysis application to find out popularity of universities based on Twitter user’s sentiment. For this purpose, we firstly collected 600 tweets datasets, which is a mixture of 200 tweets each from Princeton University, Stanford University and University of Oxford for a period of 4 days (12/1/2018 to 15/1/2018). Second, the tweets were classified based on their sentiment into “positive”, "neutral" and “negative” tweets. Finally, the results were being analyzed in terms of Precision, Recall and F1 score. These information will help universities to gather information of public sentiment towards their institution and allow them to recognize their strength and weakness. Universities can use that information to improve their public image if needed in the future.

scholarly journals Using Social Media in Tourist Sentiment Analysis: A Case Study of Andalusia during the Covid-19 Pandemic

2021 ◽  
Vol 13 (7) ◽  
pp. 3836
Author(s):  
David Flores-Ruiz ◽  
Adolfo Elizondo-Salto ◽  
María de la O. Barroso-González
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Cost Savings ◽  
Mass Scale ◽  
Tourism Sector ◽  
The Social ◽  
Analytical Tools ◽  
Media Data

This paper explores the role of social media in tourist sentiment analysis. To do this, it describes previous studies that have carried out tourist sentiment analysis using social media data, before analyzing changes in tourists’ sentiments and behaviors during the COVID-19 pandemic. In the case study, which focuses on Andalusia, the changes experienced by the tourism sector in the southern Spanish region as a result of the COVID-19 pandemic are assessed using the Andalusian Tourism Situation Survey (ECTA). This information is then compared with data obtained from a sentiment analysis based on the social network Twitter. On the basis of this comparative analysis, the paper concludes that it is possible to identify and classify tourists’ perceptions using sentiment analysis on a mass scale with the help of statistical software (RStudio and Knime). The sentiment analysis using Twitter data correlates with and is supplemented by information from the ECTA survey, with both analyses showing that tourists placed greater value on safety and preferred to travel individually to nearby, less crowded destinations since the pandemic began. Of the two analytical tools, sentiment analysis can be carried out on social media on a continuous basis and offers cost savings.

Sign in / Sign up

Export Citation Format

Share Document