EMOTION DETECTION ON KENYAN TWEETS USING EMOTION ONTOLOGY

Cleophus Kiprop Kurgat,Dr Lawrence Nderu

doi:10.47672/ejt.385

Abstract

Purpose: The purpose of the study was emotion detection on Kenyan tweets as a powerful tool in detecting and recognizing the various feelings among netizens and provide critical analytics that can be used in various platforms for decision making.Methodology: This research study adopted a descriptive research design approach. The researcher preferred this method because it allowed an in-depth study of the subject. The target population will be twitter account holders with twitter followers ranging between 100,000 up to 2000, 000 in Kenya. Data was analyzed using descriptive and inferential statistics. The study will employ a census approach to collect data from the respondents hence no sampling techniques will be used. According to Larry (2013) a census is a count of all the elements in a population. The sample size will be the 150 respondents .Quantitative data was analyzed using multiple regression analysis. The qualitative data generated was analyzed by use of Statistical Package of Social Sciences (SPSS) version 20.Results: The response rate of the study was 64%.The findings of the study indicated that hashtags, emojis, GIF’s and adjectives have a positive relationship with emotion detection in Kenya.Conclusion: R square value of 0.715 means that 71.5% of the corresponding categorization in emotion ontology can be explained or predicted by (hashtags, emojis, GIF’s and adjectives) which indicated that the model fitted the study data. The results of regression analysis revealed that there was a significant positive relationship between dependent variable and independent variable at (β = 0.715), p=0.000 <0.05).Policy recommendation: Finally, the study recommended that twitter account holders should embrace various emotion detecting platforms so as to improve how they articulate issues and further researches should to be carried out in other social media platforms to find out if the same results can be obtained.

Highlights

IntroductionHuman has ability to see emotions by temperament, disposition, personality and mood
1.1 Background of the StudyHuman has ability to see emotions by temperament, disposition, personality and mood
The first objective of the study was to assess the category of a Kenyan tweet hash tag using emotion ontology

Summary

Introduction

Human has ability to see emotions by temperament, disposition, personality and mood. Computer seeks to emulate the human emotions by digital image analysis. In some profession interaction like call centers interaction with people is important. With great advancement in technology in terms of different techniques of people interacting with each other it is quite necessary that one should be aware of current emotions of the person he/she is interacting. It is widely accepted from psychological theory that human emotions can be classified into six archetypal emotions: love, surprise, fear, anger, joy, and sadness. Facial motion and the tone of the speech play a major role in expressing these emotions (Evans, 2012)

Objectives

Methods

Results

Conclusion