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Erschienen in:
PolSentiLex: Sentiment Detection in Socio-Political Discussions on Russian Social Media Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

Predicting Eurovision Song Contest Results Using Sentiment Analysis

verfasst von : Iiro Kumpulainen, Eemil Praks, Tenho Korhonen, Anqi Ni, Ville Rissanen, Jouko Vankka

Erschienen in: Artificial Intelligence and Natural Language

Verlag: Springer International Publishing

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Abstract

Over a million tweets were analyzed using various methods in an attempt to predict the results of the Eurovision Song Contest televoting. Different methods of sentiment analysis (English, multilingual polarity lexicons and deep learning) and translating the focus language tweets into English were used to determine the method that produced the best prediction for the contest. Furthermore, we analyzed the effect of sampling tweets during different periods, namely during the performances and/or during the televoting phase of the competition. The quality of the predictions was assessed through correlations between the actual ranks of the televoting and the predicted ranks. The prediction was based on the application of an adjusted Eurovision televoting scoring system to the results of the sentiment analysis of tweets. A predicted rank for each performance resulted in a Spearman \(\rho \) correlation coefficients of 0.62 and 0.74 during the televoting period for the lexicon sentiment-based and deep learning approaches, respectively.

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Vorheriges Kapitel Unsupervised Neural Aspect Extraction with Related Terms
Nächstes Kapitel Improving Results on Russian Sentiment Datasets
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Metadaten
Titel
Predicting Eurovision Song Contest Results Using Sentiment Analysis
verfasst von
Iiro Kumpulainen
Eemil Praks
Tenho Korhonen
Anqi Ni
Ville Rissanen
Jouko Vankka
Copyright-Jahr
2020
Buch
Artificial Intelligence and Natural Language

Print ISBN: 978-3-030-59081-9

Electronic ISBN: 978-3-030-59082-6

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-59082-6_7

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