<i>ThemeScope:</i> A quantitative thematic analysis for depicting social representations in digital arenas

This article introduces ThemeScope, an analytical strategy for mapping the discursive traces of social representations across large-scale digital arenas. Grounded in social representation theory (SRT), it operationalises anchoring and objectification as discourse-analytic indicators computed ex post from co-occurrence structure and lexical concreteness. ThemeScope employs network analysis of word co-occurrences and visualisation techniques adapted from science mapping to identify and categorise lexical-thematic communities based on their structural organisation. We propose two quantitative measures to assess anchoring and objectification ex post and show the method’s interpretive potential within online discussions. This integrated framework bridges theoretical insight and computational scalability, providing a replicable approach to studying meaning-making processes in digital discourse.

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Publication Details

Journal
Journal of Information Science
Published
2026-07-17
DOI
https://doi.org/10.1177/01655515261454276
Primary Topic
Social Representations and Identity
Type
article
Field-Weighted Citation Impact
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article

ThemeScope: A quantitative thematic analysis for depicting social representations in digital arenas

Luca D’Aniello, Michelangelo Misuraca, Maria Spano
Journal of Information Science
Social Representations and Identity
article

ThemeScope: A quantitative thematic analysis for depicting social representations in digital arenas

Luca D’Aniello, Michelangelo Misuraca, Maria Spano
article en

Abstract

This article introduces ThemeScope, an analytical strategy for mapping the discursive traces of social representations across large-scale digital arenas. Grounded in social representation theory (SRT), it operationalises anchoring and objectification as discourse-analytic indicators computed ex post from co-occurrence structure and lexical concreteness. ThemeScope employs network analysis of word co-occurrences and visualisation techniques adapted from science mapping to identify and categorise lexical-thematic communities based on their structural organisation. We propose two quantitative measures to assess anchoring and objectification ex post and show the method’s interpretive potential within online discussions. This integrated framework bridges theoretical insight and computational scalability, providing a replicable approach to studying meaning-making processes in digital discourse.

Journal of Information Science
University of Salerno (IT), University of Naples Federico II (IT)
Reduced inequalities
Openalex Percentile: Top 5%
Social Representations and Identity
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