Anwar, S., & Giglietto, F. (2024). Facebook reactions in the context of politics and social issues: a systematic literature review. FRONTIERS IN SOCIOLOGY. https://doi.org/10.3389/fsoc.2024.1379265
Summary
This systematic literature review synthesizes 64 peer-reviewed studies published between 2016 and 2023 on Facebook’s Reactions feature (Love, Haha, Wow, Sad, Angry), introduced in 2016 as an expansion of the Like button. Anwar and Giglietto organize the fragmented, interdisciplinary literature into three thematic clusters — the introduction of Reactions, politics and far-right groups, and other social issues — and extract cross-study regularities via a comparative naturalistic method. The central argument is that Reactions operate as paralinguistic digital affordances that expose systematic emotional signatures of online content: lifestyle and entertainment posts skew positive, while political and controversial content elicits broader, more negative emotional profiles, with anger-driven posts consistently generating higher engagement — a pattern especially pronounced for populist and far-right actors.
Key Contributions
- First comprehensive systematic synthesis of Facebook Reactions research spanning 2016–2023 across political, social, health, and business domains.
- A thematic taxonomy that organizes an otherwise scattered interdisciplinary literature into coherent categories.
- Cross-study identification of anger as a robust driver of engagement with political and populist content.
- Diagnosis of methodological gaps: fragmented data sources, limited cross-cultural comparison, and underexplored event-based/tabloid topics.
- Research agenda pointing toward LLM-based categorization of reactions and applications in misinformation, fact-checking, and digital activism.
Methods
The authors follow Briner and Denyer’s (2012) five-step systematic review protocol: formulating questions, locating studies, selection, analysis, and reporting. Searches in Scopus, Google Scholar, and other engines were conducted monthly (July–September 2023) using combinations of “Facebook” and “Reaction” with Boolean operators, limited to peer-reviewed journal articles and conference proceedings from 2016–2023. The resulting 64 articles were thematically coded using Armstrong’s (2010) comparative naturalistic method and grouped into three macro-categories with finer sub-topics (political news, populism, healthcare, business, emotion detection).
Findings
- Distribution of the corpus: 6 articles on the introduction of Reactions, 19 on politics and far-right groups, 39 on other social issues.
- Negative appeals — especially anger — generate significantly more engagement and sharing in political campaigns (Mexico, Brexit, EU Parliament elections).
- Populist and far-right leaders receive disproportionately more Angry and Haha reactions than mainstream politicians; anger-triggering content boosts sharing.
- Hyperpartisan and junk news exhibit a bivalent logic: Love and Anger rarely co-occur, while Anger clusters with Sad and Wow.
- Reactions have been used computationally to predict emotion classes, controversy (via entropy of reaction distributions), and sentiment, though reaction-to-emotion mappings remain ambiguous — Haha and Wow can carry negative or disbelieving meanings in political contexts.
- Reactions serve as effective sentiment labels for low-resource languages (e.g., Sinhala, Bangla).
- Cultural context shapes reaction patterns (e.g., China-critical vs. China-supporting audiences in Hong Kong).
Connections
This review consolidates a strand of work in which the authors themselves have been central, including studies of Reactions and engagement with problematic information Giglietto2019-882f1900, Giglietto2020-9d8acdd7, Giglietto2020-6278a4aa, F2020-6278a4aa, as well as earlier work on Facebook’s affective architecture Iannelli2015-e0818c3e. Its emphasis on anger and negative emotion as engagement drivers for populist and far-right actors connects to research on hyperpartisan and junk news dynamics Ghezzi2023-8bebc91f and to broader debates on algorithmic amplification and exposure on Facebook Bakshy2015-rn, Gonzalez-Bailon2024-rq, Allcott2025-jb. The framing of Reactions as lightweight affective signals also speaks to work on emotional dynamics in political communication and polarization more generally Brady2026-ln, Knupfer2025-vt.