Abstract
The dissemination of disinformation and fabricated content on social media is growing. Yet little is known of what the functional Twitter data analysis methods are for languages (such as Finnish) that include word formation with endings and word stems together with derivation and compounding. Furthermore, there is a need to understand which themes linked with misinformation—and the concepts related to it—manifest in different countries and language areas in Twitter discourse. To address this issue, this study explores misinformation and its related concepts: disinformation, fake news, and propaganda in Finnish language tweets. We utilized (1) word cloud clustering, (2) topic modeling, and (3) word count analysis and clustering to detect and analyze misinformation-related concepts and themes connected to those concepts in Finnish language Twitter discussions. Our results are two-fold: (1) those concerning the functional data analysis methods and (2) those about the themes connected in discourse to the misinformation-related concepts. We noticed that each utilized method individually has critical limitations, especially all the automated analysis methods processing for the Finnish language, yet when combined they bring value to the analysis. Moreover, we discovered that politics, both internal and external, are prominent in the Twitter discussions in connection with misinformation and its related concepts of disinformation, fake news, and propaganda.
Highlights
Across disciplines, there is an increasing interest in misinformation, which is an umbrella term referring to false information circulating online [1]
The combination of computational analysis with Python and qualitative data analysis software was performed to gain a deeper understanding of the discussions related to misinformation, disinformation, fake news, and propaganda
The functional analysis methods enable the investigation of discussions on misinformation and its related concepts, such as disinformation, fake news, and propaganda themes linked with those concepts in Twitter
Summary
There is an increasing interest in misinformation, which is an umbrella term referring to false information circulating online [1]. The dissemination of disinformation and fabricated content, e.g., in the form of fake news on social media such as Twitter, is a growing concern, especially due to the lack of awareness of the existence of such false information [4,5,6,7]. Different disciplines have approached the subject of misinformation from various viewpoints of human behavior and communication, as well as the spreading enabled by information systems and social media. As examples of those presented approaches are research on cognitive biases related to information literacy [8], disinformation processing, e.g., concerning sentence comprehension and semantic decision making [9,10].
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