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dc.contributor.advisorRichter, Michael Paul Robert
dc.contributor.authorWerzner Regalado, Jordany
dc.date.accessioned2023-07-18T06:15:15Z
dc.date.available2023-07-18T06:15:15Z
dc.date.issued2021
dc.identifier.urihttps://jlupub.ub.uni-giessen.de//handle/jlupub/17802
dc.identifier.urihttp://dx.doi.org/10.22029/jlupub-17177
dc.description.abstractIn 2020 the effects of the COVID-19 pandemic and the related government-applied nationwide measures deeply influenced the Italian and Spanish population, not only financially and socially, but also in terms of the emotional state of all individuals. Due to social isolation, social media and other online communication platforms served as an outlet to express opinions and feelings about the situation and to interact with other peers. This resulted in the availability of a great amount of online data that can be utilised to analyse the sentiment and emotions expressed during this time. The aim of this study was to use this data to perform a context-based sentiment and emotion analysis in order to determine a relationship between shifting changes of sentiment and emotion and the application restriction measures in Italy and Spain. Most current studies focus on English data extracted from Twitter and show little interest towards other data sources and other languages. This thesis therefore based its analysis on over 700 000 Spanish and Italian comments extracted from the newspapers La Repubblica and El Mundo using a Pythonbased web crawler. The created press corpora represent another user demographic and can be used for the analysis of the Italian and Spanish language in other research areas. A sentiment classification algorithm based on one-layer convolutional network was used to determine the polarity in the comments. The classification method achieved an F-Score of 0.87 for the Spanish language model and an F-Score of 0.81 for the Italian model. The emotion detection was performed using the Syuzhet R Package and NRC Emotion Lexicon to create emotion scores during different time frames. Using a graphical analysis the study determined an existing emotional reaction, that could be put in relation to the measures applied by the governments. Furthermore, utilising Pearson’s correlation coefficient, it was determined that Robert Plutchik’s theory of emotional opposites applies to the analysed context. Moreover, a negative correlation was detected between the level of trust and the level of fear expressed in comments mentioning the government. All results were shown in a contrastive manner to compare the emotional reactions in the comment sections. The insights gained from this study can be used for cultural, linguistic and political analysis, political decision-making and for the development of strategies to manage the pandemic and other national catastrophes, while considering the emotional state of the population.de_DE
dc.language.isoende_DE
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSentiment Analysisde_DE
dc.subjectEmotion Detectionde_DE
dc.subjectCoronavirusde_DE
dc.subjectCovid-19de_DE
dc.subjectEmotionsanalysede_DE
dc.subjectStimmungsanalysede_DE
dc.subjectCOVID-19 pandemicde_DE
dc.subjectCOVID-19 Pandemiede_DE
dc.subjectpandemic managementde_DE
dc.subjectpress corporade_DE
dc.subjectdata analysisde_DE
dc.subjectContextual emotion analysisde_DE
dc.subjectemotional statede_DE
dc.subjectsocial isolationde_DE
dc.subjectsentiment classification algorithmde_DE
dc.subjectconvolutional networkde_DE
dc.subjectemotional reactionde_DE
dc.subjectpolitical analysisde_DE
dc.subjectcultural analysisde_DE
dc.subjectweb crawlingde_DE
dc.subjectCorpusde_DE
dc.subjectcorporade_DE
dc.subjectCorpus analysisde_DE
dc.subjectSentiment miningde_DE
dc.subjectcomputational linguisticsde_DE
dc.subjectsentiment lexiconsde_DE
dc.subjectcross-cultural analysisde_DE
dc.subjectsentiment variationsde_DE
dc.subjectweb scrapingde_DE
dc.subjectpublic opinionde_DE
dc.subjectonline discoursede_DE
dc.subjectsocial distancingde_DE
dc.subjectpandemic responsede_DE
dc.subject.ddcddc:004de_DE
dc.subject.ddcddc:070de_DE
dc.subject.ddcddc:300de_DE
dc.subject.ddcddc:310de_DE
dc.subject.ddcddc:360de_DE
dc.subject.ddcddc:400de_DE
dc.subject.ddcddc:450de_DE
dc.subject.ddcddc:460de_DE
dc.titleA sentiment analysis of Spanish and Italian news articles about COVID-19: Exploring the emotional reaction on government-applied restrictionsde_DE
dc.typemasterThesisde_DE
local.affiliationFB 05 - Sprache, Literatur, Kulturde_DE
thesis.levelmasterde_DE


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