Innovative Approaches to Survey Research and Document Analysis in Contemporary Social Research
DOI:
https://doi.org/10.31538/adrg.v6i1.3078Keywords:
Survey Research, Document Analysis, Methodological Innovation, Social Research Methods, Digital Research Methods, Research EthicsAbstract
Contemporary social research increasingly relies on survey research and document analysis, yet these methods face growing challenges arising from digitalisation, cultural diversity, data proliferation, and heightened ethical concerns. Traditional methodological frameworks, originally developed for more stable and homogeneous research contexts, are often ill-equipped to address issues such as declining response rates, interpretive bias, digital exclusion, and the epistemic implications of automated data processing. The purpose of this research is to critically examine survey research and document analysis in contemporary social research and to contribute conceptually to their methodological adaptation and innovation. Rather than generating original empirical data, the research adopts a conceptual and methodological research design grounded in critical-interpretive analysis. It draws on systematic critical engagement with existing methodological, theoretical, and interdisciplinary literature, employing conceptual synthesis and methodological critique as its primary analytical strategies. The findings reveal that many limitations associated with survey research and document analysis stem not only from technical constraints but from underlying epistemological assumptions embedded in standardisation, neutrality, and scale. The analysis further identifies emerging methodological innovations, such as adaptive survey design, AI-assisted document analysis, and reflexive ethical frameworks, as promising but requiring careful governance and contextual sensitivity. The research concludes that methodological renewal in social research must move beyond technical optimisation toward reflexive, inclusive, and ethically grounded approaches. By offering a structured conceptual framework and practical methodological guidance, this research advances methodological discourse and supports researchers in adapting established methods to complex contemporary research environments.
Downloads
References
Adeyinka, O. S. (2025). Digital and strategic qualitative research methodology. Notion Press.
Alam, M. S., Mrida, M. S. H., & Rahman, M. A. (2025). Sentiment analysis in social media: How data science impacts public opinion. Knowledge integrates natural language processing (NLP) with artificial intelligence (AI). American Journal of Scholarly Research and Innovation, 4(01), 63-100. https://doi.org/10.63125/r3sq6p80
Antoniak, M., Field, A., Mun, J., Walsh, M., Klein, L., & Sap, M. (2023, July). Riveter: Measuring Power and Social Dynamics Between Entities. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) (pp. 377-388). https://doi.org/10.18653/v1/2023.acl-demo.36
Argyres, N. S., De Massis, A., Foss, N. J., Frattini, F., Jones, G., & Silverman, B. S. (2020). History‐informed strategy research: The promise of history and historical research methods in advancing strategy scholarship. Strategic Management Journal, 41(3), 343-368. https://doi.org/10.1002/smj.3118
Atkeson, L. R., Adams, A. N., & Alvarez, R. M. (2014). Nonresponse and mode effects in self-and interviewer-administered surveys. Political Analysis, 22(3), 304-320. https://doi.org/10.1093/pan/mpt049
Behr, D., & Shishido, K. (2016). The translation of measurement instruments for cross-cultural surveys. The SAGE handbook of survey methodology, 55, 269-87. https://doi.org/10.4135/9781473957893.n19
Blumenberg, C., & Barros, A. J. (2018). Response rate differences between web and alternative data collection methods for public health research: a systematic review of the literature. International journal of public health, 63(6), 765-773. https://doi.org/10.1007/s00038-018-1108-4
Braun, V., Clarke, V., Boulton, E., Davey, L., & McEvoy, C. (2021). The online survey is a qualitative research tool. International Journal of Social Research Methodology, 24(6), 641-654. https://doi.org/10.1080/13645579.2020.1805550
Bryda, G., & Costa, A. P. (2023). Qualitative research in digital era: innovations, methodologies and collaborations. Social Sciences, 12(10), 570. https://doi.org/10.3390/socsci12100570
Calinescu, M., & Schouten, B. (2016). Adaptive survey designs for nonresponse and measurement error in multi-purpose surveys. In Survey Research Methods 10(1), 35-47.
Cheah, C. W. (2025). AI-Augmented Netnography: Ethical and Methodological Frameworks for Responsible Digital Research. International Journal of Qualitative Methods, 24, 16094069251338910. https://doi.org/10.1177/16094069251338910
Childs, S., McLeod, J., Lomas, E., & Cook, G. (2014). Opening research data: Issues and opportunities. Records management journal, 24(2), 142-162. https://doi.org/10.1108/RMJ-01-2014-0005
Christou, P. A. (2023). How to use artificial intelligence (AI) as a resource, methodological and analysis tool in qualitative research? The Qualitative Report, 28(7). https://doi.org/10.46743/2160-3715/2023.6406
Coffey, A. (2014). Analysing documents. The SAGE handbook of qualitative data analysis, 367-379. https://doi.org/10.4135/9781446282243.n25
Coffey, S., Maslovskaya, O., & McPhee, C. (2024). Recent innovations and advances in mixed-mode surveys. Journal of Survey Statistics and Methodology, 12(3), 507-531. https://doi.org/10.1093/jssam/smae025
Davie, G., & Wyatt, D. (2021). Document analysis. In The Routledge Handbook of Research Methods in the study of religion (pp. 245-255). Routledge. https://doi.org/10.4324/9781003222491-18
Dawson, P. (2014). Temporal practices: Time and ethnographic research in changing organisations. Journal of Organisational Ethnography, 3(2), 130-151. https://doi.org/10.1108/JOE-05-2012-0025
Dzogovic, S., Zdravkovska-Adamova, B., & Serpil, H. (2024). From Theory to Practice: A Holistic Study of the Application of Artificial Intelligence Methods and Techniques in Higher Education and Science. Human Research in Rehabilitation, 14(2). https://doi.org/10.21554/hrr.092406
Findley, M. G., Jensen, N. M., Malesky, E. J., & Pepinsky, T. B. (2016). Can results-free review reduce publication bias? The results and implications of a pilot study. Comparative Political Studies, 49(13), 1667-1703. https://doi.org/10.1177/0010414016655539
Gautam, V. (2021). Methodology of social research. KK Publications.
Hayes, S. (2021). Postdigital Positionality: developing powerful inclusive narratives for learning, teaching, research and policy in Higher Education. Brill. https://doi.org/10.1163/9789004466029
Hou, Y., & Huang, J. (2025). Natural language processing for social science research: A comprehensive review. Chinese Journal of Sociology, 11(1), 121-157. https://doi.org/10.1177/2057150X241306780
Javali, S., & Javali, M. S. B. (2024). A Textbook of research methodology and applied statistics. Academic Guru Publishing House.
Kara, H. (2020). Creative research methods: A practical guide. Policy Press. https://doi.org/10.56687/9781447356769
Karppinen, K., & Moe, H. (2012). What we talk about when we talk about document analysis. Trends in communication policy research: New theories, methods and subjects, 177-193. https://doi.org/10.2307/j.ctv36xvj36.12
Kellehear, A. (2020). The unobtrusive researcher: A guide to methods. Routledge. https://doi.org/10.4324/9781003137344
Khan, M. M. (2024). Optimising web surveys in research: methodological considerations and validity aspects. International Journal of Research and Scientific Innovation, 11(4), 75-105. https://doi.org/10.51244/IJRSI.2024.1104007
Kuhlthau, C. C., Maniotes, L. K., & Caspari, A. K. (2015). Guided inquiry: Learning in the 21st century. Bloomsbury Publishing USA. https://doi.org/10.5040/9798400660603
Martínez-Bravo, M. C., Sádaba Chalezquer, C., & Serrano-Puche, J. (2022). Dimensions of digital literacy in the 21st-century competency frameworks. Sustainability, 14(3), 1867. https://doi.org/10.3390/su14031867
Morgan, H. (2022). Conducting a qualitative document analysis. The qualitative report, 27(1), 64-77. https://doi.org/10.46743/2160-3715/2022.5044
Nelson, L. K., Burk, D., Knudsen, M., & McCall, L. (2021). The future of coding: A comparison of hand-coding and three types of computer-assisted text analysis methods. Sociological Methods & Research, 50(1), 202-237. https://doi.org/10.1177/0049124118769114
Niekler, A., Kahmann, C., Burghardt, M., & Heyer, G. (2023). The interactive Leipzig Corpus Miner: An extensible and adaptable text analysis tool for content analysis. Publizistik, 68(2), 325-354. https://doi.org/10.1007/s11616-023-00809-4
Ntsobi, M. P., Costa, A. P., Kasperiuniene, J., Brandão, C., & Ribeiro, J. (2024, January). Digital Tools and Techniques in Qualitative Research: Digital Skills and Research Optimisation. In World Conference on Qualitative Research (pp. 1-25). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-65735-1_1
Ozuem, W., Willis, M., Ranfagni, S., & Omeish, F. (2025). Thematic analysis in an artificial intelligence-driven context: a stage-by-stage process. International Journal of Qualitative Methods, 24, 16094069251362982. https://doi.org/10.1177/16094069251362982
Park, S., & Humphry, J. (2019). Exclusion by design: intersections of social, digital and data exclusion. Information, Communication & Society, 22(7), 934-953. https://doi.org/10.1080/1369118X.2019.1606266
Rogers, S. E. (2016). Bridging the 21st-century digital divide. TechTrends, 60(3), 197-199. https://doi.org/10.1007/s11528-016-0057-0
Rovai, A. P., Baker, J. D., & Ponton, M. K. (2013). Social science research design and statistics: A practitioner's guide to research methods and IBM SPSS. Watertree Press LLC.
Sarachuk, K. (2024, February). Scientific Text-Mining with KH Coder: Troubleshooting and Solutions. In 2024 5th International Conference on Computer Science, Engineering, and Education (CSEE) (pp. 13-17). IEEE Computer Society. https://doi.org/10.1109/CSEE63195.2024.00011
Tourangeau, R., Michael Brick, J., Lohr, S., & Li, J. (2017). Adaptive and responsive survey designs: a review and assessment. Journal of the Royal Statistical Society Series A: Statistics in Society, 180(1), 203-223. https://doi.org/10.1111/rssa.12186
Trautrims, A., Grant, D. B., Cunliffe, A. L., & Wong, C. (2012). Using the “documentary method” to analyse qualitative data in logistics research. International Journal of Physical Distribution & Logistics Management, 42(8/9), 828-842. https://doi.org/10.1108/09600031211269776
Wachsmuth, H. (2015). Text analysis pipelines. In Text Analysis Pipelines: Towards Ad-hoc Large-Scale Text Mining (pp. 19-53). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-25741-9_2
Wood, L. M., Sebar, B., & Vecchio, N. (2020). Application of rigour and credibility in qualitative document analysis: Lessons learnt from a case study. The Qualitative Report, 25(2), 456-470. https://doi.org/10.46743/2160-3715/2020.4240
Xiao, Z., Zhou, M. X., Liao, Q. V., Mark, G., Chi, C., Chen, W., & Yang, H. (2020). Tell me about yourself: Using an AI-powered chatbot to conduct conversational surveys with open-ended questions. ACM Transactions on Computer-Human Interaction (TOCHI), 27(3), 1-37. https://doi.org/10.1145/3381804
Xie, K., Vongkulluksn, V. W., Heddy, B. C., & Jiang, Z. (2024). Experience sampling methodology and technology: An approach for examining situational, longitudinal, and multi-dimensional characteristics of engagement. Educational technology research and development, 72(5), 2585-2615. https://doi.org/10.1007/s11423-023-10259-4
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Moses Adeleke Adeoye

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.





