Improved sentiment urgency emotion detection for business intelligence

Tariq Soussan*, Marcello Trovati

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)

1 Citation (Scopus)

Abstract

The impact of social media on people’s lives has significantly grown over the last decade. Individuals use it to promote discussions and a way of acquiring data. Industries use social media to market their goods and facilities, advise and inform clients about future offers, and follow up on their direct market. It also offers vital information concerning the general emotions and sentiments directly connected to welfare and security. In this work, an improved model called Improved Sentiment Urgency Emotion Detection (ISUED) has been created based on previous work for opinion and social media mining implemented with Multinomial Naive Bayes algorithm and based on three classifiers which are sentiment analysis, urgency detection, and emotion classification. The model will be trained to improve its accuracy and F1 score so that the precision and percentage of correctly predicted texts is elevated. This model will be applied on the same data set of previous work acquired from a general business Twitter account of one of the largest chains of supermarkets in the United Kingdom to be able to see what sentiments and emotions can be detected and how urgent they are.

Original languageEnglish
Title of host publicationAdvances in Intelligent Networking and Collaborative Systems - The 12th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2020
EditorsLeonard Barolli, Kin Fun Li, Hiroyoshi Miwa
Publisherspringer
Pages312-318
Number of pages7
ISBN (Print)9783030577957
DOIs
Publication statusE-pub ahead of print - 21 Aug 2020
Event12th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2020 - Victoria, Canada
Duration: 31 Aug 20202 Sep 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1263 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference12th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2020
CountryCanada
CityVictoria
Period31/08/202/09/20

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