Studying and Modeling the Connection between People's Preferences and Content Sharing

People regularly share items using online social media. However, people's decisions around sharing---who shares what to whom and why---are not well understood. We present a user study involving 87 pairs of Facebook users to understand how people make their sharing decisions. We find that even when sharing to a specific individual, people's own preference for an item (individuation) dominates over the recipient's preferences (altruism). People's open-ended responses about how they share, however, indicate that they do try to personalize shares based on the recipient. To explain these contrasting results, we propose a novel process model of sharing that takes into account people's preferences and the salience of an item. We also present encouraging results for a sharing prediction model that incorporates both the senders' and the recipients' preferences. These results suggest improvements to both algorithms that support sharing in social media and to information diffusion models.Comment: CSCW 201

Resolution limit in community detection

Detecting community structure is fundamental to clarify the link between structure and function in complex networks and is used for practical applications in many disciplines. A successful method relies on the optimization of a quantity called modularity [Newman and Girvan, Phys. Rev. E 69, 026113 (2004)], which is a quality index of a partition of a network into communities. We find that modularity optimization may fail to identify modules smaller than a scale which depends on the total number L of links of the network and on the degree of interconnectedness of the modules, even in cases where modules are unambiguously defined. The probability that a module conceals well-defined substructures is the highest if the number of links internal to the module is of the order of \sqrt{2L} or smaller. We discuss the practical consequences of this result by analyzing partitions obtained through modularity optimization in artificial and real networks.Comment: 8 pages, 3 figures. Clarification of definition of community in Section II + minor revision

Social determinants of content selection in the age of (mis)information

Despite the enthusiastic rhetoric about the so called \emph{collective intelligence}, conspiracy theories -- e.g. global warming induced by chemtrails or the link between vaccines and autism -- find on the Web a natural medium for their dissemination. Users preferentially consume information according to their system of beliefs and the strife within users of opposite narratives may result in heated debates. In this work we provide a genuine example of information consumption from a sample of 1.2 million of Facebook Italian users. We show by means of a thorough quantitative analysis that information supporting different worldviews -- i.e. scientific and conspiracist news -- are consumed in a comparable way by their respective users. Moreover, we measure the effect of the exposure to 4709 evidently false information (satirical version of conspiracy theses) and to 4502 debunking memes (information aiming at contrasting unsubstantiated rumors) of the most polarized users of conspiracy claims. We find that either contrasting or teasing consumers of conspiracy narratives increases their probability to interact again with unsubstantiated rumors.Comment: misinformation, collective narratives, crowd dynamics, information spreadin

“You’re free from just a girl or a boy”:Nonbinary children’s understanding of their gender

BackgroundIn recent years, research on gender diversity in early childhood has increased significantly. However, much of the published literature still focuses on children whose experiences align with binary gender norms, inadvertently excluding nonbinary experiences from analysis.AimsWe seek to explore how nonbinary children, aged five to eight, perceive and understand their gender modality and experiences.MethodsNine American nonbinary children were interviewed using a semi-structured approach, which included two book readings, a drawing activity, and approximately 23 pre-determined questions. Inductive reflexive thematic analysis was utilized for developing, analyzing, and interpreting patterns across a qualitative dataset. All authors engaged in various aspects of reflexivity throughout the process, including personal, functional, and disciplinary reflexivity.AnalysisWe constructed five themes, which were evident across the accounts of participating children. The first one, Being nonbinary has different meanings for different people, illustrates the diverse interpretations of nonbinary identities. Gender is hard to describe but my pronouns help me make sense of it, highlights the challenges of explaining gender, yet pronouns help participants lucidly put their and others’ gender into words. People can change their gender for good or just for a little while, reflect participants’ view of gender as dynamic and fluid. “I have the agency to decide who I am with a little help of others”: feeling, learning, choosing and telling, explores participants’ journey in adopting the label “nonbinary”. Lastly, Being nonbinary is both easy and hard: easy because I am myself, hard because of other people, depicts the multifaceted experiences of being nonbinary, from the affirmation to bullying.DiscussionIn an era marked by a contentious political climate and ongoing debates about trans/nonbinary individuals, these young children defy conventional norms and establish themselves as active architects of their identity narratives, driven by their agency and self-determination

Spreading in Social Systems: Reflections

In this final chapter, we consider the state-of-the-art for spreading in social systems and discuss the future of the field. As part of this reflection, we identify a set of key challenges ahead. The challenges include the following questions: how can we improve the quality, quantity, extent, and accessibility of datasets? How can we extract more information from limited datasets? How can we take individual cognition and decision making processes into account? How can we incorporate other complexity of the real contagion processes? Finally, how can we translate research into positive real-world impact? In the following, we provide more context for each of these open questions.Comment: 7 pages, chapter to appear in "Spreading Dynamics in Social Systems"; Eds. Sune Lehmann and Yong-Yeol Ahn, Springer Natur

XPS and water contact angle measurements on aged and corona-treated PP

Effects of corona treatment and aging on commercially produced corona discharged polypropylene (PP) films were followed via surface sensitive roughness analysis by atomic force microscopy (AFM), water contact angle (WCA), and X-ray photoelectron spectroscopic (XPS) measurements. Roughness analysis by AFM gave similar results for both untreated and corona-treated samples. The measured water contact angle decreased after corona treatment but increased with aging. XPS findings revealed that corona treatment caused an increase in the O-containing species on the surface of the films, but the measured O/C atomic ratio decreased with aging. The angle dependence of the observed XPS O/C atomic ratio further revealed that surface modifications by the corona treatment were buried into the polymer away from the surface as a function of aging. This is attributed to a surface rearrangement of the macromolecules in agreement with the findings of Garbassi et al. on oxygen-plasma-treated polypropylene

Suicide ideation of individuals in online social networks

Suicide explains the largest number of death tolls among Japanese adolescents in their twenties and thirties. Suicide is also a major cause of death for adolescents in many other countries. Although social isolation has been implicated to influence the tendency to suicidal behavior, the impact of social isolation on suicide in the context of explicit social networks of individuals is scarcely explored. To address this question, we examined a large data set obtained from a social networking service dominant in Japan. The social network is composed of a set of friendship ties between pairs of users created by mutual endorsement. We carried out the logistic regression to identify users' characteristics, both related and unrelated to social networks, which contribute to suicide ideation. We defined suicide ideation of a user as the membership to at least one active user-defined community related to suicide. We found that the number of communities to which a user belongs to, the intransitivity (i.e., paucity of triangles including the user), and the fraction of suicidal neighbors in the social network, contributed the most to suicide ideation in this order. Other characteristics including the age and gender contributed little to suicide ideation. We also found qualitatively the same results for depressive symptoms.Comment: 4 figures, 9 table

Fashion, Cooperation, and Social Interactions

Fashion plays such a crucial rule in the evolution of culture and society that it is regarded as a second nature to the human being. Also, its impact on economy is quite nontrivial. On what is fashionable, interestingly, there are two viewpoints that are both extremely widespread but almost opposite: conformists think that what is popular is fashionable, while rebels believe that being different is the essence. Fashion color is fashionable in the first sense, and Lady Gaga in the second. We investigate a model where the population consists of the afore-mentioned two groups of people that are located on social networks (a spatial cellular automata network and small-world networks). This model captures two fundamental kinds of social interactions (coordination and anti-coordination) simultaneously, and also has its own interest to game theory: it is a hybrid model of pure competition and pure cooperation. This is true because when a conformist meets a rebel, they play the zero sum matching pennies game, which is pure competition. When two conformists (rebels) meet, they play the (anti-) coordination game, which is pure cooperation. Simulation shows that simple social interactions greatly promote cooperation: in most cases people can reach an extraordinarily high level of cooperation, through a selfish, myopic, naive, and local interacting dynamic (the best response dynamic). We find that degree of synchronization also plays a critical role, but mostly on the negative side. Four indices, namely cooperation degree, average satisfaction degree, equilibrium ratio and complete ratio, are defined and applied to measure people's cooperation levels from various angles. Phase transition, as well as emergence of many interesting geographic patterns in the cellular automata network, is also observed.Comment: 21 pages, 12 figure