Abstract
A pressing societal and scientific question is how social media use affects our cognitions, emotions, and behaviors. To answer this question, fine-grained insight into the content of individuals’ social media use is needed. It is difficult to study content-based social media effects with traditional survey methods because such methods are incapable of capturing the extreme volume and variety of social media content that is shared and received. Therefore, this special issue aims to illustrate how content-based social media effects could be examined by integrating communication sciences and computational methods. We describe a three-step method to investigate content-based media effects, which involves (a) collecting digital trace data, (b) performing automated textual and visual content analysis, and (c) conducting linkage analysis. This Special Issue zooms in on these steps and describes the strengths and weaknesses of different computational methods. We conclude with some challenges that need to be addressed in future research.
| Original language | English |
|---|---|
| Pages (from-to) | 115-123 |
| Number of pages | 9 |
| Journal | Communication Methods and Measures |
| Volume | 18 |
| Issue number | 2 |
| Early online date | 27 Nov 2023 |
| DOIs | |
| Publication status | Published - 2023 |
Bibliographical note
SPECIAL ISSUE FOR COMPUTATIONAL MEDIA EFFECTS.Publisher Copyright:
© 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.
Funding
The work was supported by the\u00A0Koninklijke Nederlandse Akademie van Wetenschappen [Early career partnership grant]. A KNAW early career partnership grant awarded to J.L. Pouwels by the Royal Netherlands Academy of Arts and Sciences was used to organize an interdisciplinary expert meeting on the special issue topic. The special issue builds on insights that were obtained during this meeting.
| Funders |
|---|
| Koninklijke Nederlandse Akademie van Wetenschappen |
| Royal Netherlands Academy of Arts |
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