Open research questions in Opinion Dynamics and Social Influence
34 unresolved questions extracted from the limitations and future-work sections of 1,226 Opinion Dynamics and Social Influence papers in our library. Each links back to the study that raised it.
What the literature leaves open
Current algorithms cannot distinguish whether a click arising in the socially- based app link channel is driven by reciprocity pressure or by authentic preference, and resolving this blind spot with respect to political content is both a direction of technological advancement and a point of departure that should be examined prior to regulation.
Reinforcing the Filter Bubble–Echo Chamber Integration through Socially-Based App Links A Theoretical Inquiry into Cognitive-Style-Based Content Transfer · 2026 · DOIThis paper's recommendation rests on a theoretical framework and has not been preceded by empirical verification. The socially-based app link is one pathway this paper has specified, and it is emphasized that the causes of extremization are complex. The following additional limitations are stated explicitly. First, the very scope of "political content" is an open problem. How this boundary is set greatly alters the range to which this paper's recommendation applies, and that judgment is left to platforms. Second, the strength of the norm of reciprocity may differ across cultures. Click pressure may operate more strongly in collectivist cultures, and whether this paper's hypothesis applies identically across cultures requires separate examination. Third, while this paper explores a direction of causality in which socially-based app links reinforce extremization, the possibility that already-extremized users make greater use of this channel cannot be excluded. The direction of cause and effect cannot be asserted without empirical evidence. Fourth, this paper does not deny the existence of voluntary selective exposure driven by confirmation bias, nor the phenomenon of active echo chambers. Individual autonomous choice and algorithmic passive extremization operate on different levels. This paper's scope is limited to the structural blind spot whereby even involuntary clicks generated by reciprocity pressure are processed by the algorithm identically to authentic preferences—independent of whether individual voluntary choice is present. In the political domain in particular, individual autonomy must be respected; and it is precisely for that reason that the structural conditions under which that autonomy operates must be trustworthy. The intervention this paper proposes is not directed at individual choice itself, but at correcting a structural flaw that contaminates the informational environment in which that choice is made.
Reinforcing the Filter Bubble–Echo Chamber Integration through Socially-Based App Links A Theoretical Inquiry into Cognitive-Style-Based Content Transfer · 2026 · DOIResearch comparing shifts in the political landscape around 2015, when socially-based app links became prevalent, is needed. If the same level of extremization was observed before their introduction, the algorithm may be the principal cause; if not, the possibility that socially-based app links are a key variable can be explored. In the same vein, research comparing extremization metrics before and after the enforcement of EU Regulation 2024/900 is needed. If it can be confirmed that convergence on cognitive-style-based signals actually accelerated after explicit-category regulation, this would provide grounds for directly testing the regulatory-paradox hypothesis this paper raises. Research distinguishing, at the algorithmic level, clicks driven by the norm of reciprocity from clicks driven by authentic preference is needed. If it can be confirmed that external pressure degrades the predictive precision of behavioral signals, and the effect of excluding this noise signal on recommendation quality is empirically demonstrated, the matter could be redefined as a data-quality problem rather than a normative demand. Further, how the strength of reciprocity-driven click pressure varies by culture and group size, and whether the strength of the reinforcement loop increases nonlinearly as the group grows larger, also warrant exploration. Research is needed on whether cognitive style can be inferred through modes of hobby engagement, and on whether cognitive-style-based content transfer occurs especially strongly in cultures of support. Research comparing whether similar transfer occurs in other domains with uniform modes of engagement, beyond cultures of support, would contribute to testing the generality of the Cognitive Homophily hypothesis. Direct empirical demonstration of Cognitive Homophily may also be addressed together in this context. An experimental design is needed to verify whether filter bubbles and echo chambers are in fact integrated and reinforced through the app link channel, and whether the level of extremization decreases when behavioral signals concerning political content arising in that channel are excluded. In that prior filter-bubble-mitigation experiments did not touch the influx pathway itself, this approach may open a new direction of research. Sports fandom has, in some historical contexts, been mobilized as an instrument of political mobilization. Whether this mobilization is connected to cognitive learning through repeated exposure to group outcomes remains a subsequent task. More broadly, whether sustained participation in a culture of support—through iterative exposure to outcomes that cannot be resisted—operates as a learning mechanism that reinforces an acceptance-oriented cognitive style warrants empirical investigation.
Reinforcing the Filter Bubble–Echo Chamber Integration through Socially-Based App Links A Theoretical Inquiry into Cognitive-Style-Based Content Transfer · 2026 · DOIThe current study, however, is not without its limitations. Importantly, the social interac- tion setting in our study was online, which is a technological innovation that in some ways does not reflect in-person social interaction. Thus, some nonverbal behaviours, important to in person contexts might have been missed. For example, perceived eye-contact, which could not be measured in the current online paradigm, can contribute to favourable percep- tions of interaction partners (Hietanen et al., 2020). It is possible, therefore, that our find- ings might not generalise to an in-person context. Nevertheless, we feel confident that this online setting is an appropriate first step. First, this context allows us to isolate the face and minimise the influence of wider bodily or gestural behaviours. Second, we can record spon- taneous facial movement in great detail from a frontal video angle. Finally, and importantly, online interactions are now commonplace (Lieberman & Schroeder, 2020) and online facial expressivity correlates highly with in-person expressivity and similarly contributes to the outcomes of the social interaction (Rollings et al., 2024). We invite future research to build on our findings and consider cross-modal communication signals and their impact on social positioning during group formation. Some other methodological decisions are worth mentioning in light of possible limita- tions and future directions. In the current study data on ethnicity and cultural background was not recorded, however, cultural differences could play a role in how facial behaviours are used (McDuff et al., 2017) or interpreted (Tsai et al., 2019). As a next step, a cross- cultural comparison could shed light into how our findings translate among different cul- tural backgrounds. Further, a longitudinal approach could be used to indicate whether facial expressivity influences group-level outcomes over time. This seems plausible, as initial judgements of others have been found to be predictive of long-term friendship outcomes (Human et al., 2013) Moreover, experimental and longitudinal studies could also be used to test the causal relationship between FE and popularity as the current study’s correlational nature cannot determine directionality. Finally, we provide future studies with some consid- Journal of Nonverbal Behavior (2026) 50:233–2531 3 249 erations for improved measurement of some of the studied variables. Namely, rephrasing the behavioural intention item used to capture participants’ willingness to continue inter- action past the study’s end could be done to better reflect genuine interest, as the current wording of this item might have been confusing to participants due to the lack of actual opportunity for them to interact with each other again. Similarly, researchers are encour- aged to use multi-item measures of person-perception to improve reliability and reduce measurement error. These adjustments could strengthen the interpretability and robustness of findings in this context. To conclude, the current study is the first to consider how facial expressivity impacts social popularity during naturalistic social interaction in groups. Our findings indicate that more expressive individuals occupy more central roles within the group and are therefore more socially popular. These results support the hypothesis that facial expression functions to facilitate and maintain social connections with others. Supplementary Information The online version contains supplementary material available at h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 1 0 9 1 9 - 0 2 6 - 0 0 5 1 4 - 6 . Acknowledgements We would like to express our sincere appreciation to Olivia Keane who contributed to the data managing and preparation for analysis of this project during their position as a research assistant. Author Contributions A. B. was involved in the conceptualisation and design of the study, data collection, performing formal analysis, visualisation and data presentation, writing the original draft, reviewing and edit- ing the manuscript. E.K. was involved in the conceptualisation and design of the study, reviewing and editing of the manuscript, supervising the project, and advising data analysis. T.K. was involved in the conceptualisa- tion and design of the study, reviewing and editing of the manuscript, and supervising the project.B.W. was involved in the conceptualisation and design of the study, reviewing and editing of the manuscript, supervis- ing the project, advising data analysis and acquiring funding for the project. Data Availability The complete study processed data, and R are available on the Open Science Framework: h t t p s : / / o s f . i o / k g z 9 v / o v e r v i e w ? % 2 0 v i e w _ o n l y = 3 4 2 a 3 0 d b c 7 b c 4 4 4 8 9 e 5 d d 0 6 9 3 f a 5 2 4 d a.
Facially Expressive People are More Popular in Newly Formed Groups: A Social Network Analysis · 2026 · DOIOver the past decade, research on online behavior has revealed a growing number of empirical regularities: power-law distributions of attention, echo chambers, asymmetric exposure, and recurrent patterns of coordination. These findings, often replicated across platforms and contexts, represent an important step toward a more systematic understanding of the dynamics underlying digital interactions. Yet despite this empirical progress, the field still lacks a shared analytical framework to explain how such patterns emerge, under what conditions they persist, and how they interact with platform design. The first open challenge concerns the development of models that capture behavioral dynamics beyond idealized scenarios. Many current models remain loosely connected to empirical observables and rely on assumptions that are difficult to validate or calibrate with real-world data. More systematic efforts are needed to link model parameters to measurable quantities and to evaluate explanatory power beyond internal consistency or stylized reproduction. A second limitation lies in the difficulty of isolating the role of platform architecture. While similar behavioral phenomena appear across diverse systems, the contribution of algorithmic curation, moderation policies, and interface design remains difficult to disentangle from endogenous dynamics. Comparative studies, leveraging natural variation across platforms or temporal policy shifts, may offer a viable strategy, but require coordinated efforts in data collection and methodological design.
M. Hilbert, J. Vásquez, D. Halpern, S. Valenzuela, two step, network step? E. Arriagada, One step, complementary communication flows in twittered citizen protests, Social Science Computer Review 35 (4) (2017) 444–461. arXiv: https://doi.org/10.1177/0894439316639561, doi:10.1177/0894439316639561. URL 0894439316639561 https://doi.org/10.1177/ on E. Dubois, and leaders seekers Paquet-Labelle, S. Minaeian, A. S. Beaudry, Who to trust on social media: How opinion disinformation and echo chambers, Social Media + Society 6 (2) (2020) 2056305120913993. arXiv: https://doi.org/10.1177/2056305120913993, doi:10.1177/2056305120913993. URL 2056305120913993 https://doi.org/10.1177/ avoid communication, The ANNALS of J. B. Manheim, The one-step W. L. Bennett, the flow of American Academy of Political and Social Science 608 (1) arXiv:https: //doi.org/10.1177/0002716206292266, doi:10.1177/0002716206292266. URL 0002716206292266 https://doi.org/10.1177/ (2006) 213–232. A. Broder, R. Kumar, F. Maghoul, P. Raghavan, S. Rajagopalan, R. Stata, A. Tomkins, J. Wiener, Graph structure in the web, Computer Networks (2000). doi: 10.1016/S1389-1286(00)00083-9. R. Yang, L. Zhuhadar, O. Nasraoui, Bow-tie decomposition in directed graphs, 2011. M. Bernaschi, A. Celestini, M. Cianfriglia, S. Guarino, F. Lombardi, E. Mastrostefano, Onion under microscope: An in-depth analysis of the tor web, World Wide Web 25 (3) (2022) 1287–1313. doi:10.1007/s11280-022-01044-z. URL s11280-022-01044-z http://dx.doi.org/10.1007/ S. Vitali, J. B. Glattfelder, S. Battiston, The network of global corporate control, PLOS ONE 6 (10) (2011) 1–6. doi:10.1371/journal.pone.0025995. URL https://doi.org/10.1371/journal.pone. 0025995 K. Jamieson, J. Cappella, Echo Chamber: Rush Limbaugh and the Conservative Media Establishment, Oxford University Press, 2008. N. Ayi, N. P. Duteil, Mean-field and graph limits for collective dynamics models with time-varying weights, Journal of Differential Equations 299 (2021) 65–110. R. K. Garrett, Echo chambers online?: Politically motivated selective exposure among internet news users, Journal of Computer-Mediated Communication 14 (2009) 265–285. doi:10.1111/J.1083-6101. 2009.01440.X. C. A. Bail, L. P. Argyle, T. W. Brown, J. P. Bumpus, H. Chen, M. B. F. Hunzaker, J. Lee, M. Mann, F. Merhout, A. Volfovsky, Exposure to opposing views on social media can increase political polarization, Proceedings of the National Academy of Sciences 115 (37) (2018) 9216–9221. doi:10.1073/pnas.1804840115. URL http://dx.doi.org/10.1073/pnas. 1804840115 M. Cinelli, G. De Francisci Morales, A. Galeazzi, W. Quattrociocchi, M. Starnini, The echo chamber effect on social media, Proceedings of the national academy of sciences 118 (9) (2021) e2023301118. G. De Francisci Morales, C. Monti, M. Starnini, interactions (2021) 2818. No echo in the chambers of political on reddit, Scientific Reports 11 (1) doi:10.1038/s41598-021-81531-x. URL s41598-021-81531-x https://doi.org/10.1038/ C. Monti, J. D’Ignazi, M. Starnini, G. De Francisci Morales, Evidence of demographic rather than ideological segregation in news discussion on in: Proceedings of the ACM Web Conferreddit, ence 2023, WWW ’23, ACM, 2023, p. 2777–2786. doi:10.1145/3543507.3583468. URL 3583468 http://dx.doi.org/10.1145/3543507. S. Guarino, F. Pierri, M. D. Giovanni, A. Celestini, Information disorders during the covid-19 infodemic: The case of italian facebook, Online Social Networks and Media 22 (2021) 100124. doi:10.1016/J.OSNEM. 2021.100124. R. Berner, T. Gross, C. Kuehn, J. Kurths, S.
Do social norms really matter, or are they just behavioral idiosyncrasies that become associated with a group? Social norms are generally considered as a collection of formal or informal rules, but where do these rules come from and why do we follow them? The definition for social norm varies by field of study, and how norms are established and maintained remain substantially open questions across the behavioral sciences.
Processes of self-organization of network communities and the functioning of social networks in this context is an absolutely unique phenomenon that leads social development and humanity, however, it hides certain risks and shortcomings that are still insufficiently explored and need in-depth analysis.
By utilizing agent-based modeling, we find that ICT-improved connectivity not only scales down collective action if the distribution of political preference is insufficiently dispersed, but it also slows the diffusion speed if the overall propensity to participate is not strong.
But little is known about how groups choose specific alliance partners; that is, who works with whom? Social embeddedness theory suggests that the social location of groups in issue networks affects the information available to them about potential partners and the desirability of particular alliances.
<i>Issue Networks, Information, and Interest Group Alliances: The Case of Wisconsin Welfare Politics, 1993-99</i> · 2004 · DOIFuture research should investigate the comparative vulnerability to influence of strangers and groups of friends in crowds, individual differences in susceptibility to crowd influence and discontinuities in individual behavior associated with changes in crowd size and proportion of crowd members already responding.
The approximate model, is an explanation for part of the improvement in the mean of the total group on iteration; but a significant amount of improvement remains to be explained. to assert The first approximate model is insufficient to explain why the total group is more accurate than the holdouts on round two.
Future research could explore adaptive threshold determination methods. A large-scale group decision-making model with no consensus threshold based on social network analysis.
Future research should explore and analyze decision-making behaviors, including uncoop- erative [51] and manipulative actions [52].
A Two-Stage Group Decision Making Model Based on Influence Game in Social Trust Network: a Cooperative Game Perspective · 2026 · DOIThe authors acknowledge that changing human psychological behavior en masse is not easy in practice, but do not provide guidance on how their theoretical findings could be translated into real-world policy implementations.
Modified Axelrod model showing opinion convergence and polarization in scale-free networks · 2026 · DOIThe model assumes agents are selected randomly or by network centrality rank, but does not explore how different selection mechanisms for empathetic agents might affect polarization reduction outcomes.
Modified Axelrod model showing opinion convergence and polarization in scale-free networks · 2026 · DOIThe paper does not explore other possible interventions beyond introducing empathetic agents to reduce opinion polarization, limiting the scope of practical solutions investigated.
Modified Axelrod model showing opinion convergence and polarization in scale-free networks · 2026 · DOIThe model assumes finite memory of past opinions and abrupt external shocks, but extensions could explore more complex memory mechanisms or gradual shock profiles.
The comparison with the 2014 and 2018 Brazilian elections, while qualitatively supportive, does not constitute quantitative validation of the model.
I tackle an old question, which has received a revived interest with the rise of social media: what drives opinion polarisation? There is no consensus in both the empirical and the theoretical literature about how to model, measure and investigate Opinion heterogeneity.
While previous studies have consistently demonstrated that individuals are more willing to gossip about norm deviations, existing research has understudied the potential role of the group membership of gossip target (i.
Why did this upsurge of protests occur beyond the antinuclear concerns? The exact mechanism that caused this general upsurge of protests has not been explored in detail.
Connections result in a general upsurge of protests: egocentric network analysis of social movement organizations after the Fukushima Nuclear Accident · 2020 · DOIFurthermore, previous research on the impact of scheduling is scarce, partially due to a lack of a common taxonomy with which to discuss and compare schedules.
Agent Scheduling in Opinion Dynamics: A Taxonomy and Comparison Using Generalized Models · 2019 · DOIAlthough empirical findings show a strong correlation between this phenomenon and modularity of a social network, still little is known about the actual mechanisms driving communities to conflicting opinions.
The Interplay Between Conformity and Anticonformity and its Polarizing Effect on Society · 2016 · DOIStill, the unique role that interest groups play in policy diffusion networks is not fully understood, in large part because the current methodology for studying diffusion cannot parse out interest group influence.
Most-cited papers in Opinion Dynamics and Social Influence
- Dynamics of Networks if Everyone Strives for Structural Holes · American Journal of Sociology · 2008 · 222 citations
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- Trust exploration- and leadership incubation- based opinion dynamics model for social network group decision-making: A quantum theory perspective · European Journal of Operational Research · 2024 · 86 citations
- Interest Group Influence in Policy Diffusion Networks · State Politics & Policy Quarterly · 2015 · 86 citations
- Slow response times undermine trust in algorithmic (but not human) predictions · Organizational Behavior and Human Decision Processes · 2020 · 83 citations
- Adaptive opinion dynamics over community networks when agents cannot express opinions freely · Neurocomputing · 2024 · 63 citations
- Information Cascades and Social Learning · Journal of Economic Literature · 2024 · 61 citations
- Higher-order interactions shape collective human behaviour · Nature Human Behaviour · 2025 · 61 citations
- Spiral of Silence in the Social Media Era: A Simulation Approach to the Interplay Between Social Networks and Mass Media · Communication Research · 2019 · 59 citations
Most recent work
- Analytical Sociology. Generative Models, Mechanisms, Explanations · KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie · 2026
- Opinion dynamics under electoral shocks in competitive campaigns · International Journal of Modern Physics C · 2026
- Opinion dynamics: Statistical physics and beyond · Reviews of Modern Physics · 2026
- Modified Axelrod model showing opinion convergence and polarization in scale-free networks · International Journal of Modern Physics C · 2026
- Decision Similarity Effect In Social Relativity Theory · Zenodo (CERN European Organization for Nuclear Research) · 2026
- Forecasting Public Sentiments via Mean Field Games · SIAM Journal on Applied Mathematics · 2026
- Optimal Control of Opinion Dynamics on Complex Networks via Discounted LQR: Theory and Computation · Mathematics · 2026
- Social Power Games for Parallel Friedkin–Johnsen Models · IEEE Transactions on Automatic Control · 2026
- When cardinals strategize: An agent-based model of influence and ideology for the papal conclave · Chaos Solitons & Fractals · 2026
- Mathematical Modeling of Opinion Dynamics under Algorithmic Amplifications: A Bifurcation Analysis · Black Sea Journal of Engineering and Science · 2026
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