Rethinking Public Opinion Studies In The Digital Era: Expert Discourse On The Theoretical And Methodological Challenges Of Public Opinion Research

Purpose Social media platforms provide the most dynamic environment for creating, disseminating, and sharing political information and opinions (Kraft et al., 2020). In addition, they provide fertile ground for increasingly diverse and multidimensional forms of public opinion formation, shaped by various leaders, including those who are not human. The impact of algorithmization and the use of artificial intelligence on shaping the political attitudes of internet users forces scholars to redefine and recategorize public opinion (Gandini et al., 2025). Furthermore, researchers need to resolve the problem of measuring public opinion in the era of digital communication (Baden et al., 2020). In this paper, we aim to address the theoretical and methodological challenges that scholars studying public opinion face today. Our analysis was guided by the following two research questions: (RQ1) What challenges do experts encounter when conducting research on public opinion in the digital age? (RQ2) How do they envision the future of the field in the evolving landscape? Design/methodology/approach This study employs a survey-based methodology to investigate the experiences and perspectives of public opinion scholars in the context of transformations related to social media and artificial intelligence. A questionnaire was distributed among scholars from the COST OPINION network and respondents recommended by the network through the snowball method. The survey yielded 86 completed questionnaires from experts across 33 countries, representing various disciplines (linguistics, media and communication, political science, IT, etc.). After initial screening, 82 valid questionnaires were retained for analysis. The questionnaire consisted of 15 substantive questions and three socio-demographic questions. The first part of the questionnaire was designed to collect information on the profile of scholars studying public opinion. Specifically, we aimed to identify their primary area of professional expertise, their experience in public opinion research, methodological approach, and the methods they employ in their studies. Additionally, we collected information on perceived challenges associated with theoretical concepts and the design of the studies on public opinion, including those triggered by AI and algorithms. To further explore the challenges experts face, we employed thematic analysis of answers to the open-ended question on the perceived future of the field. Through an inductive coding approach, we identified and categorized themes, providing insights into the methodological and theoretical challenges of public opinion research in the digital era. Findings Our study showed that the more experienced the scholars were, the more they perceived challenges in public opinion research. Senior researchers with more than nine years of experience in their field primarily focus on methodological precision, emphasizing the design of questions and the selection of samples as critical challenges. This suggests that while learning, scholars become more concerned about survey design and representative sampling to trust the validity and reliability of public opinion research. Early-career researchers, including doctoral students, postdoctoral fellows, and those with less than nine years of experience, often face challenges related to respondent bias and dataset complexity as they continue to navigate reducing bias in responses and managing large datasets. Such a strong focus on respondent bias highlights the challenges of creating neutral, unbiased questions and interpreting respondents' responses without the influence of social desirability or cognitive bias. Furthermore, data massification, characterized by an overflow of digital public opinion data, presents a more significant impediment to early-career scholars, who often lack the necessary tools to process and analyze large-scale data. We also noticed that different academic viewpoints within various disciplines influence the understanding of difficulties and AI-generated risks. Scholars from the fields of law and political science are concerned with regulatory frameworks, democratic processes, and political communication, and their research primarily focuses on misinformation and the dissemination of inauthentic content. The focus of computer scientists on public opinion fragmentation, data-related challenges associated with big data analytics, social media algorithms, and AI-driven content personalization may be attributed to their involvement with big data analysis, social media algorithms, and AI-relevant content personalization. The problem of public discourse fragmentation is a key interest to them because algorithmic sorting and online information bubbles create widespread audience bias and isolate social discussion. However, scholars in the communication and media studies domain manage to bridge these perspectives and regard the dangers of information misinformation and the impact of such narratives via AI as fundamental in the interdisciplinary conversation of AI in the constitution of public opinion. The thematic analysis highlighted a dual challenge for scholars and experts: addressing technical methodological hurdles while rethinking theoretical frameworks for public opinion research in the digital era. Scholars widely acknowledged the importance of AI and machine learning in processing large datasets from social media, enabling real-time sentiment tracking and trend identification. However, concerns were raised about over-reliance on these tools, particularly sentiment analysis, due to methodological and theoretical gaps. Consequently, a key debate of the future of public opinion research centers on balancing AI’s potential with scientific rigor. Originality/value In this paper, we will discuss challenges and recommendations on data sampling and inclusivity, data access and privacy, data quality, and the use of methods and tools. By collecting experience and ideas from scholars across disciplines, we aim to trace similarities and differences among them. Furthermore, we strive to map the discourse of political communication experts on the challenges of public opinion research.