Citizen science in the social sciences and humanities: the power of interdisciplinarity

The paper addresses the underrepresentation and contested status of social sciences and humanities (SSH) within predominantly natural science–oriented citizen science (CS). Despite CS’s growth and ambitions for sustainability transitions, participatory innovation, and scientific literacy, SSH involvement remains less visible due to historical ties to positivist natural sciences, epistemological and methodological sensitivities of SSH topics, and technocratic funding and institutional trends. The study’s overarching question is the current and potential role of SSH in CS practice: how SSH can provide methodological frameworks, added value, and interdisciplinary synergies to CS, and how a closer bond between CS and SSH may change research practices and citizen involvement. The authors propose that SSH can democratize science, empower citizens, and inform policy, and set out to map where SSH meets or diverges from natural and biomedical sciences in CS through a meta-synthesis of published cases.

Background literature shows CS is predominantly conducted in life and natural sciences, with only a small fraction in SSH (e.g., European survey suggesting >80% natural/life sciences vs ~11% SSH). Prior work also indicates most listed CS projects are contributory (~99%), with few examples of active citizen roles via participatory action or collective intelligence. Debates concern the legitimacy of SSH, neoliberal/technocratic pressures in academia, and ethical/epistemological challenges in ‘sensitive’ SSH topics. SSH has a long tradition in participatory research and offers epistemic and methodological contributions to CS, yet terminological nuances (e.g., broader meanings of “science” in non-English contexts) complicate discovery. Policy perspectives and principles emphasize active citizen contribution, but SSH practices and visibility within CS remain limited. The literature motivates examining SSH’s locus, interdisciplinary synergies, and benefits of citizen-generated data within CS.

The study employs a qualitative meta-synthesis approach to integrate knowledge across diverse studies on CS involving SSH. Five research questions guide analysis: (1) methodological approaches and citizen roles in SSH-related CS; (2) SSH disciplinary fields and interdisciplinary synergies; (3) SSH topics attracting CS; (4) purposes for incorporating SSH in CS; (5) benefits of citizen-generated data. The analytical framework (Table 1) comprises units such as research questions, methods (overall and for citizen involvement), citizen roles in the research cycle, fields of science (stated and assigned), aims, theoretical assumptions, data types collected, raw data availability, publicizing practices, and added value for citizens. Searches were conducted in two multidisciplinary databases (Clarivate Analytics Core Collection and EBSCOhost) using a controlled two-keyword combination strategy (e.g., citizen science AND social sciences), with retrievals in October 2018 and January 2019. A total of 2763 records were identified. Limiting to on-site accessible full texts yielded 1244 papers. Titles, abstracts, and keywords were screened for relevance (explicit CS or related terms; field of science). This produced 344 full-text papers (English, Spanish, French) for preliminary meta-synthesis. Papers lacking sufficient information or being meta-analyses focusing only on outcomes were used for context but not as raw data. The team divided papers by expertise (humanities, social, biomedical, natural sciences) and used a standardized spreadsheet to extract analytical units. Through iterative discussion and critical appraisal of rigor and completeness, the final sample comprised 62 papers: 39 in social sciences, 5 in humanities, 16 combining SSH with natural sciences, and 2 combining SSH with biomedical sciences (one paper overlapped sets). Coding reliability was addressed through multidisciplinary team discussions. In-text codes denote fields: SSP (social sciences), HP (humanities), BSP (biomedical), NSP (natural sciences).

- Sample composition: 62 papers total; 39 social sciences (SSP), 5 humanities (HP), 16 SSH-natural sciences (NSP), and 2 SSH-biomedical (BSP). One paper overlapped SSP and BSP. - Social sciences: Research questions often demand-driven and oriented to societal needs. Methods span conventional (literature review, surveys, interviews, focus groups, content analysis) and innovative (digital storytelling, action research, participatory research, crowdsourcing, social dilemma games). Citizen involvement mainly via digital tools (mobile apps, 3D web, sensors/platforms); occasional in-person engagement (gamified experiments, talks, media). Citizen roles are predominantly contributory (data collection); few involve citizens across the full research cycle. Schools are typical sites of involvement. - Interdisciplinarity in SSP: 11 unique sub-fields identified (e.g., anthropology, communication, education, geography, political science, psychology, sociology, management, public policy, urban studies/planning, STS). Many papers combine multiple fields (N≈20) and sub-fields (N≈30); environmental sciences frequently appear as inherently interdisciplinary. Sociology was the most frequent sub-field (14 papers). Project aims cluster into facets: methodological (e.g., co-design, open innovation, data quality), managerial (risk communication, post-event management, marketing), policy development, social/ecological challenges (e.g., urban agriculture), social life and practices, technology’s influence, cognition/ethics/regulation/history. - Purposes/theory in SSP: Social-psychological theories link biological/health outcomes to socio-cultural-economic contexts; critical social sciences critique commodification/neoliberalism; co-creation/co-design frameworks inform citizen involvement; epistemic analyses value local/indigenous knowledge and non-expert expertise, building trust and situated, transdisciplinary knowledge. - SSP citizen-generated data: Predominantly personalized social/behavioral, attitudinal/opinion, self-reported practices, mobility patterns, risk/hazard information, community change, and sociodemographics; also marketing/consumer data. Raw data access often unspecified (majority); some provide online platforms, project sites/blogs, repositories, or personalized reports; a few interactive visualizations. Publicizing often unspecified; when stated, via open-access papers, project websites, social media, knowledge exchange. Reported citizen benefits include active scientific roles, topic awareness, training-derived expertise, empowerment for personal/community action and policy engagement, inspiration/innovation in personal/professional domains, and occasionally monetary or token rewards. - Humanities: Focus on society’s involvement in collecting/processing/analyzing sources; crowdsourcing in digitization (transcription, georeferencing, annotation); platforms often list top-down natural science projects emphasizing data quantity. CS-related questions are meta-level (science-society relations, boundaries of professional science, education). Methods: case studies, literature reviews, content analysis, surveys, interviews, typology comparisons, historical document studies. Citizen roles include data collection, documentation, mapping/georeferencing, annotation/transcription, and site recovery using local knowledge. Purposes include increased coverage, access to unpublished/local sources, accelerating research progress and data capture, improving conservation and ensuring data validity. Data types: images, transcriptions, structured community data, personal stories/local knowledge, environmental data, rainfall observations; raw data usually made available online and via platforms. Added value: heritage identity and community building, relationships and knowledge exchange with researchers, methodological accessibility and data control, immediate publication/credit, skill acquisition (e.g., TEI), increased academic literacy, and ‘social’ rewards. - Biomedical (SSH links scant): Qualitative analyses (thematic, ethnography). Citizen inputs include personal/social data and perspectives on health, culture, and governance of expert knowledge. Interdisciplinarity noted with environmental health and ethnology, applying Traditional Ecological Knowledge to link environmental factors, exposome, and social determinants of health. Citizens reframed from patients to participants/instigators of their health management. Specifics on data sharing/publicizing largely absent, but benefits include improved health-related decision capacity and learning about ethical/legal aspects of genomic data sharing. - Natural sciences (with SSH components): Mixed methods common; qualitative approaches (focus groups, interviews, participatory workshops) and combinations with surveys. Some projects involve co-producing web platforms. Citizen roles often limited to data collection; a few involve citizens in experiment design and project development or gather citizen concerns about new technologies. Many projects are top-down; some bottom-up exist. Data ownership/access often unspecified. Added value includes awareness-raising and integration of data into resource management; explicit recognition of the need for social science expertise for co-creation, evaluation, and addressing motivations/communication. - Cross-cutting: Social sciences are often ‘invisible’ within interdisciplinary CS (not explicitly labeled), whereas humanities papers explicitly state their field. Citizen data access and public communication are inconsistently addressed; accidental data reuse benefits (e.g., geospatial or social media–derived data) emerge when data are openly available. Claims about awareness-raising are common; rigorous assessments of behavior/cognition change are rare.

The findings show SSH’s strong but uneven presence in CS: social sciences are frequently embedded within interdisciplinary projects addressing complex, ‘wicked’ socio-environmental issues, yet are often not explicitly labeled, reducing visibility. Humanities participation is present but comparatively rarer and often framed through crowdsourcing and meta-analyses of CS practice/history. Across fields, citizen roles largely remain contributory, with limited engagement across the full research cycle. Nevertheless, SSH frameworks and methods demonstrably enrich CS by valuing situated and indigenous knowledge, addressing ethics and governance, and enabling co-creation and evaluation—thereby directly answering the research question about SSH’s methodological and added-value contributions. Gaps identified—unclear data accessibility/ownership, limited theorization of citizen motivations, and scarce evaluation of learning and behavior change—underscore where SSH can further enhance CS practice. Strengthening SSH integration can improve CS’s social relevance, inclusivity, and policy impact, particularly for sustainability and health domains where socio-technical dynamics are central.

The study concludes that SSH in CS is inherently interdisciplinary, frequently ‘married’ to environmental and natural sciences and, to a lesser extent, biomedical sciences. Despite CS’s potential to leverage SSH’s reflective and participatory strengths, SSH—especially the humanities—remain underutilized and less visible. Social sciences contribute both by studying CS practices and conducting citizen social science projects, while humanities contributions, though impactful for identity, community building, and academic literacy, are rarer. To maximize CS’s sustainability and societal impact, SSH frameworks should be more proactively applied to unpack socio-technical challenges (e.g., climate change, biodiversity loss), and social science methodologies should be used to better understand participants’ motivations and learning to increase self-efficacy and project outcomes. Future research should broaden evidence bases (databases, grey literature), develop shared ontologies for CS, improve communication of CS results and data back to participants, and rigorously assess learning and behavior change.

- Small and uneven sample across fields, notably only two SSH–biomedical synergy papers and five humanities papers, limiting generalizability. - Terminological variability of ‘citizen science’ across communities and languages may have led to missed studies, especially in SSH where the term is less common. - Database constraints: only Clarivate Analytics Core Collection and EBSCOhost were used; disciplines differ in publication strategies, and important outputs (e.g., monographs, edited volumes, some online journals common in humanities) are underrepresented, likely omitting relevant work. - Access limitations to full texts influenced the sampling (on-site availability), potentially biasing the corpus. - Many reviewed studies provided incomplete reporting on analytical units (e.g., data access/ownership, publicizing), restricting depth of synthesis.