Opinion dynamics: models, extensions and external effects

Recently, social phenomena have received a lot of attention not only from social scientists, but also from physicists, mathematicians and computer scientists, in the emerging interdisciplinary field of complex system science. Opinion dynamics is one of the processes studied, since opinions are the drivers of human behaviour, and play a crucial role in many global challenges that our complex world and societies are facing: global financial crises, global pandemics, growth of cities, urbanisation and migration patterns, and last but not least important, climate change and environmental sustainability and protection. Opinion formation is a complex process affected by the interplay of different elements, including the individual predisposition, the influence of positive and negative peer interaction (social networks playing a crucial role in this respect), the information each individual is exposed to, and many others. Several models inspired from those in use in physics have been developed to encompass many of these elements, and to allow for the identification of the mechanisms involved in the opinion formation process and the understanding of their role, with the practical aim of simulating opinion formation and spreading under various conditions. These modelling schemes range from binary simple models such as the voter model, to multi-dimensional continuous approaches. Here, we provide a review of recent methods, focusing on models employing both peer interaction and external information, and emphasising the role that less studied mechanisms, such as disagreement, has in driving the opinion dynamics. [...]Comment: 42 pages, 6 figure

Stationarity of the inter-event power-law distributions

A number of human activities exhibit a bursty pattern, namely periods of very high activity that are followed by rest periods. Records of these processes generate time series of events whose inter-event times follow a probability distribution that displays a fat tail. The grounds for such phenomenon are not yet clearly understood. In the present work we use the freely available Wikipedia's editing records to unravel some features of this phenomenon. We show that even though the probability to start editing is conditioned by the circadian 24 hour cycle, the conditional probability for the time interval between successive edits at a given time of the day is independent from the latter. We confirm our findings with the activity of posting on the social network Twitter. Our results suggest that there is an intrinsic humankind scheduling pattern: after overcoming the encumbrance of starting an activity, there is a robust distribution of new related actions, which does not depend on the time of day at which the activity started

Stationarity of the inter-event power-law distributions

A number of human activities exhibit a bursty pattern, namely periods of very high activity that are followed by rest periods. Records of these processes generate time series of events whose inter-event times follow a probability distribution that displays a fat tail. The grounds for such phenomenon are not yet clearly understood. In the present work we use the freely available Wikipedia's editing records to unravel some features of this phenomenon. We show that even though the probability to start editing is conditioned by the circadian 24 hour cycle, the conditional probability for the time interval between successive edits at a given time of the day is independent from the latter. We confirm our findings with the activity of posting on the social network Twitter. Our results suggest that there is an intrinsic humankind scheduling pattern: after overcoming the encumbrance of starting an activity, there is a robust distribution of new related actions, which does not depend on the time of day at which the activity started

Monogenic Diabetes in Overweight and Obese Youth Diagnosed with Type 2 Diabetes: The TODAY Clinical Trial

Purpose Monogenic diabetes accounts for 1–2% of diabetes cases. It is often undiagnosed, which may lead to inappropriate treatment. This study was performed to estimate the prevalence of monogenic diabetes in a cohort of overweight/obese adolescents diagnosed with type 2 diabetes (T2D). Methods: Sequencing using a custom monogenic diabetes gene panel was performed on a racially/ethnically diverse cohort of 488 overweight/obese adolescents with T2D in the TODAY clinical trial. Associations between having a monogenic diabetes variant and clinical characteristics and time to treatment failure were analyzed. Results: Over four percent (22/488) had genetic variants causing monogenic diabetes (7 GCK, 7 HNF4A, 5 HNF1A, 2 INS, and 1 KLF11). Patients with monogenic diabetes had a statistically, but not clinically, significant lower BMI Z-score, lower fasting insulin, and higher fasting glucose. Most (6/7) patients with HNF4A variants rapidly failed TODAY treatment across study arms (HR=5.03, p=0.0002), while none with GCK variants failed treatment. Conclusions: Discovery of 4.5% of patients with monogenic diabetes in an overweight/obese cohort of children and adolescents with T2D suggests monogenic diabetes diagnosis should be considered in children and adolescents without diabetes-associated autoantibodies and maintained C-peptide, regardless of BMI, as it may direct appropriate clinical management

Supplementary Material for: Long-Term Retention of Young Adult Study Participants with Youth-Onset Type 2 Diabetes: Results from the TODAY2 Study

Introduction: The Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) trial examined the effects of three treatment arms in a group of racially and ethnically diverse adolescents and youth with type 2 diabetes mellitus. TODAY2 was an observational follow-up study reporting outcomes and complications in these participants after having diabetes for approximately 13 years. Participant retention was essential to fulfill this objective. This report describes motivations and problems participants self-reported related to continuing in this study. Methods: The TODAY2 retention survey was administered to participants, mean age 27 years, 36% non-Hispanic Black, 18% non-Hispanic white, 39% Hispanic, 52% public and 35% private healthcare coverage, who completed the last study visit (63.8% of original TODAY cohort). The survey listed potential benefits and barriers to staying in the trial. Participants indicated agreement or disagreement with each statement using a four point Likert-type scale. Results: More than 93% of survey responders agreed with benefits listed for staying in TODAY2. The most cited reason for staying in the study was related to the strong relationship that participants had with study staff. The common barriers to attending trial visits were: tending to other medical problems, fear of disappointing study staff, and school/work scheduling conflicts. Participants with public healthcare coverage were more likely to endorse benefits related to diabetes care (e.g. getting latest test results, staying motivated to care for my diabetes) and monetary compensation, whereas participants with poor glycemic control cited that a barrier to attending study visits was “fear of disappointing” study staff. Discussion/Conclusion: In a racially and ethnically diverse population of youth-onset type 2 diabetes, benefits and barriers associated with long-term retention are described. These findings can be used to help inform future retention strategies for young adults in clinical trials