Abstract
Spectator journals published during the Age of Enlightenment served to enhance morality of readers and focused on a plethora of topics, such as the image of women or men, politics and religion. Although spectator journals have been studied extensively, little is known about the sentiment that they express. In this paper, we analyze text sentiment of spectator journals published in four different languages during a time period of over one hundred years. For that, we conduct (i) a sentiment analysis and (ii) analyze sentiment networks, for which we compute and investigate various network metrics, such as degree distributions and clustering coefficients. Additionally, we study the commonalities and differences between negative and positive words according to the respective metrics. Our results depict a high variability in positive and negative word usage and their linking patterns and extend our knowledge of spectator journals published during the Age of Enlightenment.
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Notes
- 1.
Code available at https://github.com/philkon/sentiment-spectator.
- 2.
- 3.
- 4.
https://spacy.io (version used: 2.1.3).
- 5.
- 6.
See our GitHub for complete lists of top hundred central words per language.
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Acknowledgements
Parts of this work were funded by the go!digital programme of the Austrian Academy of Sciences. Further, we want to thank Alexandra Fuchs, Bernhard Geiger, Elisabeth Hobisch, Martina Scholger and further members of the DiSpecs project for their fruitful input during the conduction of our experiments.
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Koncar, P., Helic, D. (2020). Text Sentiment in the Age of Enlightenment. In: Cherifi, H., Gaito, S., Mendes, J., Moro, E., Rocha, L. (eds) Complex Networks and Their Applications VIII. COMPLEX NETWORKS 2019. Studies in Computational Intelligence, vol 882. Springer, Cham. https://doi.org/10.1007/978-3-030-36683-4_29
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