Abstract
This paper aims to present a methodology for monitoring and assessing the public perception of security on social media, given the great importance of security in determining the people’s well-being. The methodology is applied to different corpora obtained by collecting Twitter messages about three topics of the agenda setting related to security. It operates in two steps, in the first one, ETM is performed in order to identify topic representation and sentiment. In the second step, this information is transformed in a stream of numerical data and a composite index aggregates the information on the sentiment related to the three topics. The composite index embeds a penalty function, which reduces the weight of the sequences, which show the greatest volatility over time. Results show that this procedure allows for real-time measurement of the perception of security, which is mostly negative. It is net of the effect of communication hype, and it enables to quantify reliably any potential change in the public perception.
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Notes
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The first eight words of the cluster ordered by their occurrences in the cluster are: minister, children, before, student, school, clandestine, protect, education.
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The first ten words of the cluster ordered by their occurrences in the cluster are: editor, arrest, need, editor’s company, truth, know, cheat, government, country, spy.
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The first ten words of the cluster ordered by their occurrences in the cluster are: war, humanity, to commit, to remember, to look, to pay, to find, trafficking in human beings, world, international.
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Greco, F., Polli, A. Security Perception and People Well-Being. Soc Indic Res 153, 741–758 (2021). https://doi.org/10.1007/s11205-020-02341-8
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Keywords
- Public perception
- Security
- Wellbeing
- Emotional text mining
- Composite index