Computational Sociology Research Papers - Academia.edu (original) (raw)

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- Sociology, Computational Sociology, Media Studies, Social Media

Social relationships such as friendship and partner choice are ruled by the proximity principle, which states that the more similar two individuals are, the more likely they will become friends. However, proximity, similarity, and friendship are concepts with blurred edges and imprecise grades of membership. This study shows how to simulate these friendship dynamics in an agent-based model that applies fuzzy sets theory to implement agent attributes, rules, and social relationships, explaining the process in detail. Although in principle it may be thought that the use of fuzzy sets theory makes agent-based modelling more elaborated, in practice it saves the modeller from taking some arbitrary decisions on how to use crisp values for representing properties that are inherently fuzzy. The consequences of applying fuzzy sets and operations to define a fuzzy friendship relationship are compared with a simpler implementation, with crisp values. By integrating agent computational models and fuzzy set theory, this paper provides useful insights into scholars and practitioners to tackle the uncertainty inherent to social relationships in a systematic way.

This paper proposes a computer simulation framework for investigating the role of built form – specifically physical venues-in the dynamics of neighborhood integration and segregation. Looking to Schelling's classic work (1971) and the subsequent literature, we note, however, that with few exceptions 'form' in these models is reduced to an agent's capacity to 'see' nearby grid-cells of the simulation world: an agent's neighbourhood is its Moore neighbourhood. In this research, we argue that an analytically meaningful simulation of neighbourhood formation – or more specifically of integration and segregation dynamics – must acknowledge the role of built form. To do so, we introduce physical venues into the classic Schelling model in order to reconsider the simulation's dynamics as influenced by both the spaces where agents live and the spaces of their activities. Our analysis proceeds through a series of four case studies of increasing sophistication, considering the impact of different spatial configurations as well as different kinds of venue. We articulate a simple but powerful generative model of urban social formations that also may offer insight into the conditions under which sedimented patterns of segregation may become unsettled.

- by Daniel Silver
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- Computational Sociology, Urban Planning, Urban Studies, Urban Sociology

How do illegal markets grow and develop? Using unique transaction-level data on 7,205 market actors and 16,847 illegal drug exchanges on a “darknet” drug market, the authors evaluate the network processes that shape online illegal drug trade and promote the growth of online illegal drug markets. Contrary to past research on online markets, the authors argue that the high-risk context of illegal trade enhances market actors’ reliance on social relationships that emerge endogenously from transaction networks. The findings reveal a highly structured trade network characterized by dense clustering and frequent recurrent drug exchange. Dynamic network models reveal that both embeddedness and closure in exchange structure increase the hazard rate of illegal drug trade, with effect sizes comparable to formal reputations. These effects are pronounced in the early stages of market development but wane once the market reaches maturity. These findings demonstrate the powerful, temporally contingent, influence of transaction networks on illegal trade in online markets and reveal how endogenous networks of economic relations can promote risky exchange under conditions of relative anonymity and illegality.

- by Dana L Haynie and +1
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- Sociology, Computational Sociology, Economic Sociology, Social Networks

How do social ties in online worlds evolve over time?
This research examined the dynamic processes of
relationship formation, maintenance, and demise in a
massively multiplayer online game. Drawing from evolutionary
and ecological theories of social networks, this
study focuses on the impact of three sets of evolutionary
factors in the context of social relationships in the
online game EverQuest II (EQII): the aging and maturation
processes, social architecture of the game, and
homophily and proximity. A longitudinal analysis of tie
persistence and decay demonstrated the transient
nature of social relationships in EQII, but ties became
considerably more durable over time. Also, character
level similarity, shared guild membership, and geographic
proximity were powerful mechanisms in preserving
social relationships.

- by Cuihua Shen
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- Computational Sociology, Social Networks, Multiplayer Online Games, Big Data

We introduce a conceptual-mathematical model that simulates the spread of information. We represent the states of the actors in the information flow using compartments. The compartment diagram is translated into a system of coupled ordinary differential equations. The diversity of social groups (subpopulations) is incorporated in the model, and the model is applicable for a heterogeneous community. We determine four possible spots that can be influenced to control the information propagation such as (1) controlling the inflow and outflow of people in each subpopulation, (2) regulating the media of communication, (3) influencing the belief system of the actors, and (4) introducing an antithesis to the circulating information.

The development of the web has increased the diversity of pornographic content, and at the same time the rise of online platforms has initiated a new trend of quantitative research that makes possible the analysis of data on an unpreced- ented scale. This paper explores the application of a quantitative approach to publicly available data collected from pornographic websites. Several analyses are applied to these digital traces with a focus on keywords describing videos and their underlying categorization systems. The analysis of a large network of tags shows that the accumulation of categories does not separate scripts from each other, but instead draws a multitude of significant paths between fuzzy categories. The datasets and tools we describe have been made publicly available for further study.

- by Antoine Mazieres
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- Computational Sociology, Data Mining, Web Science, Pornography Studies

É possível falar em uma programação da comunicação humana? Esta dissertação tem como objetivo compreender o papel algorítmico em rede na sociedade contemporânea, principalmente como agentes automatizados – conhecidos como robôs (bots) – atuaram no Twitter nas Eleições Presidenciais do Brasil em 2014. Consideramos que, com a quantidade de dados em larga escala (big data), esse agenciamento recíproco entre atores humanos e não humanos é ativado através do processamento de dados e da mediação no ambiente das redes sociais. Sendo assim, ponderamos que o fluxo de dados em grande quantidade é composto em caráter associativo entre agentes humanos e artificiais. Nossa hipótese é que esses atores em relação implicam novas práticas comunicacionais e acabam por transformar os espaços públicos de interação nas redes sociais (como Twitter e Facebook) criando uma cultura da massificação e notificação. Por meio de um método quali-quantitativo que une a cartografia e a teoria dos grafos, é possível coletar, analisar e visualizar os rastros produzidos pelos usuários das redes sociais. Na medida em que dialogamos com referências teóricas na filosofia, antropologia, comunicação, computação e literatura, buscamos compreender a escala em que o bot enquanto ferramenta algorítmica altera o nosso modo de comunicar e as implicações na esfera digital. A nossa análise das Eleições Presidenciais de 2014 tem como base dados coletados do Twitter durante debates eleitorais e a última semana do pleito. Desse modo, nossa discussão problematiza o bot como um agente algorítimico capaz de interferir no modo como o social se faz.

- by Lorena Regattieri
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- Computational Sociology, Anthropology, Communication, Media Studies

The urban policy mobility literature describes the widespread circulation of policy ideas while highlighting their mutations along the way. At the same time, the literature often analyzes the localization of such ideas by examining their adoption in one or several cities. To better understand policy replications and mutations, we develop theoretical and methodological strategies that provide sensitivity to both local distinctiveness and global variability. We build on the Urban Policy Mobility literature and combine it with ecological theories of conceptual spaces to develop the concept of Urban Model Spaces – a matrix of discursive possibilities evolving from the accumulated replications and localizations of a model. We articulate it via three core properties central to Urban Policy Mobility - Temporality, Scale, and Position and test how they shape the emergence of policy discourses. To demonstrate the concept we analyze public art policy and the funding mechanism of the Percent for Art ordinance from 26 cities combining Structural Topic Modeling and regression analysis

- by Daniel Silver
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- Computational Sociology, Sociology of Culture, Cultural Policy, Public Art

How do illegal markets grow and develop? Using unique transactionlevel data on 7,205 market actors and 16,847 illegal drug exchanges on a "darknet" drug market, the authors evaluate the network processes that shape online illegal drug trade and promote the growth of online illegal drug markets. Contrary to past research on online markets, the authors argue that the high-risk context of illegal trade enhances market actors' reliance on social relationships that emerge endogenously from transaction networks. The findings reveal a highly structured trade network characterized by dense clustering and frequent recurrent drug exchange. Dynamic network models reveal that both embeddedness and closure in exchange structure increase the hazard rate of illegal drug trade, with effect sizes comparable to formal reputations. These effects are pronounced in the early stages of market development but wane once the market reaches maturity. These findings demonstrate the powerful, temporally contingent, influence of transaction networks on illegal trade in online markets and reveal how endogenous networks of economic relations can promote risky exchange under conditions of relative anonymity and illegality. Governments play a key role in market development. States define the type of products for sale as well as the rules governing exchange. Markets also rely on

- by Scott Duxbury and +1
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- Computational Sociology, Economic Sociology, Social Networks, Trust

In this article, we present results on the identification and behavioral analysis of social bots in a sample of 542,584 Tweets, collected before and after Japan's 2014 general election. Typical forms of bot activity include massive Retweeting and repeated posting of (nearly) the same message, sometimes used in combination. We focus on the second method and present (1) a case study on several patterns of bot activity, (2) methodological considerations on the automatic identification of such patterns and the prerequisite near-duplicate detection, and (3) we give qualitative insights into the purposes behind the usage of social/political bots. We argue that it was in the latency of the semi-public sphere of social media—and not in the visible or manifest public sphere (official campaign platform, mass media)—where Shinz o Abe's hidden nationalist agenda interlocked and overlapped with the one propagated by organizations such as Nippon Kaigi and Internet right-wingers (netto uyo) during the election campaign, the latter potentially forming an enormous online support army of Abe's agenda.

Hecho en México 5 ÍNDICE Agradecimientos Prefacio Capítulo 1 Introducción a la modelación y simulación en ciencia política 1.1. Objeto de estudio en la ciencia política 1.2. Cambio de paradigma en la investigación social y política 1.3. Sistemas complejos: sociales y políticos 1.4. Dos asuntos para modelar y simular 1.4.1. Desobediencia civil y rebeliones urbanas 1.4.2. Opinión pública Capítulo 2 Modelado basado en agentes 2.1. ¿Qué es la modelación basada en agentes? 2.2. Protocolo ODD 2.3. Software para el modelado basado en agentes 2.3.1. Modelo de Schelling en NetLogo 2.3.2. Modelo de Schelling en MatLab Capítulo 3 Modelo de desobediencia civil de Epstein 3.1. Modelando la desobediencia civil 6 3.2. Definición y propiedades del modelo de Epstein 3.3. Protocolo ODD del modelo de desobediencia civil 3.3.1. Visión general 3.3.2. Conceptos del diseño (design concepts) 3.3.3. Detalles (details) 3.4. Resultados de las simulaciones 3.4.1. Legitimidad del gobierno L = 1 3.4.2. Legitimidad del gobierno L = 0.5 3.4.3. Legitimidad del gobierno L = 0.1 3.4.4. Legitimidad del gobierno L = 0 3.4.5. Cambios en la legitimidad del gobierno 3.5. Interpretación sociopolítica del modelo Capítulo 4 Modelo de formación de opinión pública 4.1. Modelando la opinión pública 4.2. Definición y propiedades del modelo de opinión pública 4.3. Protocolo ODD del modelo de opinión 4.3.1. Visión general 4.3.2. Detalles (details) 4.4. Resultados de las simulaciones 4.4.1. Sociedad de incertidumbre media inicial U = 0.2 4.4.2. Sociedad de incertidumbre media inicial U = 0.5 4.5. Interpretación sociopolítica del modelo Apéndice Bibliografía 7 AGRADECIMIENTOS Todo trabajo de investigación es producto de una serie de acontecimientos y voluntades. Este texto no es la excepción. La colaboración y el compromiso de los autores en los temas presentados hacen que éste sea una primera aportación al trabajo reflexivo y crítico sobre la modelación de fenómenos sociopolíticos. Un acontecimiento que contribuyó de forma extraordinaria a la elaboración de este texto fue la estancia posdoctoral de la Dra. Norma L. Abrica Jacinto en El Colegio de San Luis, A.C. Dicha estancia no habría sido posible sin el apoyo económico e institucional del Consejo Nacional de Ciencia y Tecnología (Conacyt), que otorgó una beca de estancia posdoctoral mediante la solicitud 2018-000005-01NACV-01077. Asimismo, agradecemos al Dr. Julio César Contreras Manrique, quien apoyó desde la coordinación del Programa de Estudios Políticos e Internacionales de El Colegio de San Luis, A.C., durante el proceso de la estancia posdoctoral. Finalmente, agradecemos la revisión minuciosa de los dictaminadores anónimos, quienes con sus pertinentes comentarios nos ayudaron a perfeccionar el texto.

- by Antonio Aguilera Ontiveros and +1
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- Computational Sociology, Computational Social Sciences

Recent methodological debates in sociology have focused on how data and analyses might be made more open and accessible, how the process of theo- rizing and knowledge production might be made more explicit, and how developing means of visualization can help address these issues. In ethnogra- phy, where scholars from various traditions do not necessarily share basic epistemological assumptions about the research enterprise with either their quantitative colleagues or one another, these issues are particularly complex. Nevertheless, ethnographers working within the field of sociology face a set of common pragmatic challenges related to managing, analyzing, and pre- senting the rich context-dependent data generated during fieldwork. Inspired by both ongoing discussions about how sociological research might be made more transparent, as well as innovations in other data-centered fields, the authors developed an interactive visual approach that provides tools for addressing these shared pragmatic challenges. They label the approach “ethnoarray” analysis. This article introduces this approach and explains how it can help scholars address widely shared logistical and technical complexities, while remaining sensitive to both ethnography’s epistemic diversity and its practitioners shared commitment to depth, context, and interpretation. The authors use data from an ethnographic study of serious illness to construct a model of an ethnoarray and explain how such an array might be linked to data repositories to facilitate new forms of analysis, inter- pretation, and sharing within scholarly and lay communities. They conclude by discussing some potential implications of the ethnoarray and related approaches for the scope, practice, and forms of ethnography.

- by Corey M . Abramson
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- Computational Sociology, Epistemology, Research Methodology, Ethnography

This paper provides an overview on the impact of agent-based models in the social sciences. It focuses on the reasons why agent-based models are seen as important innovations in the recent decades. It is aimed to evaluate the impact of this innovation on various disciplines, such as economics, sociology, anthropology, and behavioural sciences. It discusses the advances it contributed to achieve and illustrates some comparatively new fields to which it gave rise. Finally, it emphasizes some research issues that need to be addressed in the future. have been crucial in the creation of a scientific community of abm scientists.

This paper investigates the relationship between methodological individualism (MI) and agent-based simulation (ABS). We use a thesis defended by Caterina Marchionni and Petri Ylikoski (2013) as the starting point of our approach. According to this thesis, since MI is often considered to be a reductionist orientation, it is confusing and meaningless to assume that ABS, which is a non-reductionist and emergentist explanatory model, is committed to MI. We criticise this view and focus on the problem of the proper definition of MI. We explain that MI is compatible with the ABS strategy because reductionism is only the most simplistic variant of MI and argue that ABS explanations must be regarded as explanations in terms of non-reductionist MI.

- by Francesco Di Iorio and +1
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- Computational Sociology, Computational Economics, Austrian Economics, Multiagent Systems

This paper provides an overview on the impact of agent-based models in the social sciences. It focuses on the reasons why agest-based models are seen as important innovations in the recent decades. It is aimed to evaluate the impact of this innovation on various disciplines, such as economics, sociology, anthropology, and behavioural sciences. It discusses the advances it contributed to achieve and illustrates some comparatively new fields to which it gave rise. Finally, it emphasizes some research issues that need to be addressed in the future.

Purpose À The authors apply topic sentiment analysis (several relatively new text analysis methods) to the study of public opinion as expressed in social media by comparing reactions to the Trayvon Martin controversy in spring 2012 by... more

- by Gabe Ignatow and +1
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- Sociology, Computational Sociology, Sentiment Analysis, Correspondence Analysis

- by Samer Hassan
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- Sociology, Computational Sociology, Applied Mathematics, Friendship

This note discusses two challenges to simulating the social process of science. The first is developing an adequately rich representation of the underlying Data Generation Process which scientific progress can "learn". The second is how to get effective data on what, in broad terms, the properties of the "future" are. Paradoxically, with due care, we may learn a lot about the future by studying the past.

We discuss in this paper an agent political belief in Malaysia. Worldview map is used as the belief. Inter-agent interaction propagates the belief throughout the agent population, subject to similarity of emotion between the interacting agents and their distances apart, and various attributes of the individual extend their reach. Computational experiments made using the model point to its plausibility. Further, it highlights, for the ruling coalition, the importance of both a strong political pro machinery and a strong governance in winning the hearts and minds of the electorate.

Computational sociology models social phenomena using the concepts of emergence and downward causation. However, the theoretical status of these concepts is ambiguous; they suppose too much ontology and are invoked by two opposed sociological interpretations of social reality: the individualistic and the holistic. This paper aims to clarify those concepts and argue in favour of their heuristic value for social simulation. It does so by proposing a link between the concept of emergence and Luhmann's theory of communication. For Luhmann, society emerges from the bottom-up as communication and he describes the process by which society limits the possible selections of individuals as downward causation. It is argued that this theory is well positioned to overcome some epistemological drawbacks in computational sociology.

- by Mauricio Salgado
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- Sociology, Computational Sociology, Social Systems Theory, Social Simulation

We propose that late modern policing practices, that rely on neighbourhood intelligence, the monitoring of tensions, surveillance and policing by accommodation , need to be augmented in light of emerging 'cyber-neighbourhoods', namely social media networks. The 2011 riots in England were the first to evidence the widespread use of social media platforms to organise and respond to disorder. The police were ill-equipped to make use of the intelligence emerging from these non-terrestrial networks and were found to be at a disadvantage to the more tech-savvy rioters and the general public. In this paper, we outline the development of the 'tension engine' component of the Cardiff Online Social Media ObServatroy (COSMOS). This engine affords users with the ability to monitor social media data streams for signs of high tension which can be analysed in order to identify deviations from the 'norm' (levels of cohesion/low tension). This analysis can be overlaid onto a palimpsest of curated data, such as official statistics about neighbourhood crime, deprivation and demography, to provide a multidimensional picture of the 'terrestrial' and 'cyber' streets. As a consequence, this 'neighbourhood informatics' enables a means of questioning official constructions of civil unrest through reference to the user-generated accounts of social media and their relationship to other, curated, social and economic data.

- by Adam Edwards
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- Computational Sociology, Criminology, Social Work, Social Media

Introduction Voluntary organisations provide essential
support to vulnerable populations and front-line
health
responders to the COVID-19 pandemic. The French
Red Cross (FRC) is prominent among organisations
offering health and support services in the current crisis.
Comprised primarily of lay volunteers and some trained
health workers, FRC volunteers in the Paris (France) region
have faced challenges in adapting to pandemic conditions,
working with sick and vulnerable populations, managing
limited resources and coping with high demand for their
services. Existing studies of volunteers focus on individual,
social and organisational determinants of motivation, but
attend less to contextual ones. Public health incertitude
about the COVID-19 pandemic is an important feature of
this pandemic. Whether and how uncertainty interacts with
volunteer understandings and experiences of their work
and organisational relations to contribute to Red Cross
worker motivation is the focus of this investigation.
Methods and analysis This mixed-methods
study will
investigate volunteer motivation using ethnographic
methods and social network listening. Semi-structured
interviews and observations will illuminate FRC volunteer
work relations, experiences and concerns during the
pandemic. A questionnaire targeting a sample of Paris
region volunteers will allow quantification of motivation.
These findings will iteratively shape and be influenced
by a social media (Twitter) analysis of biomedical and
public health uncertainties and debates around COVID-19.
These tweets provide insight into a French lay public’s
interpretations of these debates. We evaluate whether and
how socio-political
conditions and discourses concerning
COVID-19 interact with volunteer experiences, working
conditions and organisational relations to influence
volunteer motivation. Data collection began on 15 June
2020 and will continue until 15 April 2021.
Ethics and dissemination The protocol has received
ethical approval from the Institut Pasteur Institutional
Review Board (no 2020-03). We will disseminate findings
through peer-reviewed
articles, conference presentations
and recommendations to the FRC.

- by Leonardo Heyerdahl
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- Computational Sociology, Anthropology, Infodemiology, Infodemic

Environmental sociology is a growing field producing a diverse body of literature while also moving into the mainstream of the larger discipline. The twin goals of this paper are to introduce environmental sociologists to innovations in content analysis, specifically a form of text-mining known as topic modeling, and then employing it to identify key themes and trends within our diverse field. We apply the topic modeling approach to a corpus of research articles within environmental sociology, identifying 25 central topics within the field and examining their prevalence over time, co-occurrence, impact (judged by citations), and prestige (judged by journal rankings). Our results indicate which topics are most prevalent, tend to occur together, and how both vary over time. They also indicate that the highest impact topics are not the most prevalent, the most prestigious topics are not the most prevalent, and topics can be prestigious without exerting much impact. We conclude with a discussion of the capabilities computational text analysis methods offer environmental sociologists.

- by Jeremiah Bohr and +1
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- Computational Sociology, Environmental Sociology, Computational Social Science, Topic Models

Ethnographic research identifies brokering (a.k.a., "copping for others") as an important and popular way people who use heroin acquire the drug by making purchases for their peers. Brokering is when a customer buys drugs for a fellow customer using the buyer's money and is paid using drug the buyer purchases. This distributes heroin costs. Heroin dealers obviously manipulate price and/or drug purity to make profits and compete for buyers, but a hidden way they alter "price" is by adjusting the size of heroin packages they sell. Using an agent-based model, we simulate brokering and heroin package resizing to understand how these dynamics influence heroin consumption costs. High rates of dealer arrest are tested against these dynamics. Findings indicate the Quantity-Adjusted Price of heroin is greater than its retail price in all conditions, implying increased competition in heroin markets does not lower costs.

- by Lee Hoffer
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- Computational Sociology, Drugs and drug culture, Drug Addiction

Is it possible use algorithms to find trends in the history of popular music? And is it possible to predict the characteristics of future music genres?
In order to answer these questions, we produced a hand-crafted dataset with the intent to put together features about style, psychology, sociology and typology, annotated by music genre and indexed by time and decade. We collected a list of popular genres by decade from Wikipedia and scored music genres based on Wikipedia descriptions. Using statistical and machine learning techniques, we find trends in the musical preferences and use time series forecasting to evaluate the prediction of future music genres.

- by Fabio Celli
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- Computational Sociology, Music, Musicology, Natural Language Processing

Framing is a sophisticated form of discourse in which the speaker tries to induce a cognitive bias through consistent linkage between a topic and a specific context (frame). We build on political science and communication theory and use probabilistic topic models combined with time series regression analysis (autoregressive distributed-lag models) to gain insights about the language dynamics in the political processes. Processing four years of public statements issued by members of the U.S. Congress, our results provide a glimpse into the complex dynamic processes of framing, attention shifts and agenda setting, commonly known as "spin". We further provide new evidence for the divergence in party discipline in U.S. politics.

- by Oren Tsur and +1
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- Computational Sociology, Natural Language Processing, Political Science, Computational Social Science

In the first part of this essay (Perspectives, Fall
2015), I suggested things are looking pretty
good for sociological theory, an optimism
grounded in my appreciation of emergent
sociological sub-fields where interesting
theoretical work is being paired with
innovative new measurement regimes to
create different kinds of sociological insights. I
pointed to the field of computational sociology
(or Big Data social science) as an example. In
this second part, I offer a few reasons why I
think this area of research will continue to
need more and better theory in the years
ahead. I highlight three causes, what I call: (1)
the paradigm effect, (2) the data effect, and (3)
the culture effect.

- by John W Mohr
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- Computational Sociology, Sociological Theory, Big Data

Social relationships such as friendship and partner choice are ruled by theproximity principle, which states that the more similar two individuals are, the more likely they will become friends. However, proximity, similarity, and friendship are concepts with blurred edges and imprecise grades of membership. This study shows how to simulate these friendship dynamics in an agent-based model that appliesfuzzy sets theoryto implement agent attributes, rules, and social relationships, explaining the process in detail. Although in principle it may be thought that the use of fuzzy sets theory makes agent-based modelling more elaborated, in practice it saves the modeller from taking some arbitrary decisions on how to use crisp values for representing properties that are inherently fuzzy. The consequences of applying fuzzy sets and operations to define a fuzzy friendship relationship are compared with a simpler implementation, with crisp values. By integrating agent computational models and ...

- by Juan Pavón
- •
- Sociology, Computational Sociology, Applied Mathematics, Friendship

In a groundbreaking article, Moody and White (2003) introduced the concept of structural cohesion, simultaneously characterizing emergent communities and their internally embedded layers by the number of node-independent paths interconnecting individuals. Like many studies, however, they “corrected” the directionality discovered in some of their data. While often done for important purposes, doing so potentially confounds structural cohesion with unrelated concepts. Some relations, especially those relating to the dynamic aspects of social life, are inherently directed, in whole or in part, and it may prove worthwhile to respect this directionality. In this article, I recast structural cohesion in terms of directed social relations and identify four distinct ways of measuring it. In two example data sets—hiring relations among graduate programs and trust relations among neighborhood residents—I show that only strong embeddedness, a type of structural cohesion emerging from directed relations, proves to be a powerful, robust, independent explanatory factor. I further show that if the directionality in the data in these examples had been “corrected,” the importance of structural cohesion would have been dramatically undervalued.

- by Noga Keidar
- •
- Computational Sociology, Sociology of Culture, Human Geography, Cultural Policy

Long-standing results in urban studies have shown correlation of population and population density to a city’s pace of life,
empirically tested by examining whether individuals in bigger cities walk faster, spend less time buying stamps, or make greater
numbers of telephone calls. Contemporary social media presents a new opportunity to test these hypotheses. This study
examines whether users of the social media platform Twitter in larger and denser American cities tweet at a faster rate than
their counterparts in smaller and sparser ones. Contrary to how telephony usage and productivity scale superlinearly with city
population, the total volume of tweets in cities scales sublinearly. This is similar to the economies of scale in city infrastructures
like gas stations. When looking at individuals, however, greater population density is associated with faster tweeting. The
discrepancy between the ecological correlation and individual behavior is resolved by noting that larger cities have sublinear
growth in the number of active Twitter users. This suggests that there is a more concentrated core of more active users that
may serve an information broadcast function for larger cities, an emerging group of “town tweeters” as it were.

- by Dhiraj Murthy
- •
- Computational Sociology, Human Dynamics, Twitter, Urban Culture

If the global brain is a suitable model of the future information society, then one future of research in this global brain will be in its past, which is its distributed memory. In this paper, we draw on Francis Heylighen, Marta Lenartowicz, and Niklas Luhmann to show that future research in this global brain will have to reclaim classical theories of social differentiation in general and theories of functional differentiation in particular to develop higher resolution images of this brain's function and sub-functions. This claim is corroborated by a brain wave measurement of a considerable section of the global brain. We used the Google Ngram Viewer, an online graphing tool which charts annual counts of words or sentences as found in the largest available corpus of digitalized books, to analyse word frequency time-series plots of key concepts of social differentiation in the English as well as in the Spanish, French, German, Russian, and Italian sub-corpora between 1800 and 2000. The results of this socioencephalography suggest that the global brain's memory recalls distinct and not yet fully conscious biases to particular sub-functions, which are furthermore not in line with popular trend statements and self-descriptions of modern societies. We speculate that an increasingly intelligent global brain will start to critically reflect upon these biases and learn how to anticipate or even design its own desired futures.

- by Steffen Roth and +4
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- Computational Sociology, Digital Humanities, Capitalism, Social Systems Theory

In some ways, the balancing of theory and practice is always needed, but that need is also, I think, more pronounced in some places and at some times than others. My sense is that the embrace of edgy theory-infused empirical work is on the upswing in sociology, and I think this bodes well for sociological theory. I say this in part because I have been watching a number of new research programs coming into formation where scholars are finding the headroom to bring broad, smart, and interesting theorizing to bear on problems that are deeply embedded in, and indeed constitutive of, the design and conceptualization of the empirical work itself. Often, this research is more exploratory than confirmatory, and, as I will try to explain here with regard to the case of the new field of computational sociology, I think we can identify some of the reasons why this is happening more frequently now than before.

- by John W Mohr
- •
- Computational Sociology, Text Mining, Sociological Theory, Big Data

idea general del libro 1 3 La idea del modelado basado en agentes en la sociología computacional 1 4 La economía computacional basada en agentes 1 5 La teoría computacional de las organizaciones Capítulo II Modelado basado en agentes 2 1 ¿Qué son los sistemas basados en agentes? 2 2 Inteligencia artificial distribuida 2 3 Agentes por todos lados 2 4 Modelos basados en agentes versus otras formas de modelar 2 5 Aleatoriedad versus determinismo 2 6 ¿Cuándo es un modelo basado en agentes más adecuado? Capítulo III Descripción del modelo 3 1 Describiendo y formulando modelos basados en agentes 3 2 El protocolo ODD: ¿qué es? y ¿por qué usarlo? 3 3 Protocolo ODD: descripción general 3 3 1 Propósito 3 3 2 Entidades, variables de estado y escalas 3 3 3 Descripción general de los procesos y programación 3 4 Protocolo ODD:

- by Colin Drayton
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- Computational Sociology, Anthropology, Social Networks, Information Theory

We present a new agent-based model for the simulation of tax compliance and tax evasion behaviour (SIMULFIS). The main novelties of the model are the introduction of a 'behavioural filter approach' to model tax decisions, the combination of a set of different mechanisms to produce tax compliance (namely rational choice, normative commitments, and social influence), and the use of the concept of 'fraud opportunity use rate' (FOUR) as the main behavioural outcome. After describing the model in detail, we display the main behavioural and economic results of 1,920 simulations calibrated for the Spanish case and designed to test for the internal validity of SIMULFIS. The behavioural outcomes show that scenarios with strict rational agents strongly overestimate tax evasion, while the introduction of social influence and normative commitments allows to generate more plausible compliance levels under certain deterrence conditions. Interestingly, the relative effect of social influence is shown to be ambivalent: it optimizes compliance under low and middle deterrence conditions, but not when deterrence is made harder. Finally, SIMULFIS economic outcomes are broadly in line with theoretical expectations, December 21, 2012 11:7 WSPC/INSTRUCTION FILE ACS˙SimulFIS 2 Llacer, Miguel, Noguera & Tapia thus supporting the reliability of the model.

- by Lee Hoffer
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- Computational Sociology, Computational Social Science

This article presents Networked Pantheon, a relational database of biographies of globally famous people spanning the last 5,500 years of human history. This source of information is intended to complement Pantheon 1.0 (Yu et. al. 2016), a biographical dataset that includes temporal, spatial, gender, and occupational information on 11,341 world-renowned people-defined as those who have their biographies in 25 or more Wikipedia language-versions-. Networked Pantheon adds information about the biographical links between these historical figures, which was compiled from the hyperlinks between the biographies in English Wikipedia. This digital method allows technics from network analysis to be used to study the relationships between globally famous people, and thus to calculate different measures of historical centrality for individuals, cities, countries, genders, and occupations. Networked Pantheon complements the historical popularity indicators of Pantheon 1.0 with measurements of the centrality of the figures in the network of biographical references, allowing for an approximation to the information flows between different territories, genders, and occupations of famous people over time.

- by Pablo Beytía
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- Computational Sociology, Historical Sociology, Digital Humanities, Social Networks
- by Abdul Ahmed III
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- Computational Sociology, Political Science, Agent-Based Modelling

In this paper, we approach the nationwide issue of high school dropouts, specific to the case study of Montgomery County Public Schools, a large school system in the Washington D.C. metro area. Utilizing data from this school district, we create a scalable ranking system that will allow MCPS to target their interventions to individuals most immediately at risk for dropping out of high school. Through our analysis, we show how techniques from machine learning provide a more effective tool for school administrators compared to their current methods. We suggest pathways for current policy improvement and additional avenues for future research.
We prepared the data by imputing missing values first on the individual level, then using the class means where individual imputation wasn’t possible. We generated binary features to replace the categorical features and generated some new features of our own. We tested a variety of machine learning classifiers on the first cohort using K-Folds cross-validation and found that logistic regression and random forest gave us the best results. Using those two classifiers, we tested on the second cohort of data and evaluated our model using precision-recall curves and found that logistic regression was the best classifier in terms of both recall and precision.

- by Joshua Gary Mausolf and +2
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- Computational Sociology, Education, Machine Learning, Computational Social Science

This paper investigates the relevance of reputation to improve the explorative capabilities of agents in uncertain environments. We have presented a laboratory experiment where sixty-four subjects were asked to take iterated economic investment decisions. An agent-based model based on their behavioural patterns replicated the experiment exactly. Exploring this experimentally grounded model, we studied the effects of various reputational mechanisms on explorative capabilities at a systemic level. The results showed that reputation mechanisms increase the agents' capability for coping with uncertain environments more than individualistic atomistic exploration strategies, although the former does entail a certain amount of false information inside the system.

ABSTRACT This article demonstrates how a technique called Agent-Based Modelling can address a significant challenge for effective interdisciplinarity. Different disciplines and research methods make divergent assertions about what a satisfactory explanation requires. However, without a unified framework analysing the implications of these differences systematically, debate cannot transcend mere competing assertion. Using a sequence of examples, I demonstrate that Agent-Based Modelling provides such a unified framework by showing how pairs of models may display quantitatively distinct behaviours when differing only in (for example) including a social network. The ability to quantify differences arising from divergent assumptions about what models should include makes them subject to empirical evaluation (rather than mere contention). Although the article uses social network examples for accessible presentation, the approach of building paired models is quite general and can, therefore, illuminate other significant social science controversies (like the role of rationality and the importance of ethnographic detail).

- by Edmund Chattoe-Brown
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- Sociology, Computational Sociology, Criminology, Psychology

Our traditional image of government is often of the Parliament or of bricks and mortar government service delivery offices, such as NHS hospitals or Benefits Agency sites. However, in an online world, government is increasingly seen and experienced through the internet. Moreover, in the online world, government websites can be readily connected into hyperlink networks. What do the online 'footprints' of social policy domains look like? And how do these online social policy networks relate to equivalent offline networks? This paper examines these questions in relation to three policy domains in the United Kingdom, namely: foreign affairs, health and education. It draws on large scale web crawls and sophisticated web metrics and Social Network Analysis techniques to map and compare the shapes of these different policy domains. It explores the shape, nature and make up of these various online networks and the participants in them, including the relevant contribution of non government and commercial websites. It considers whether or not online networks may reflect or contribute to social policy networks, or government ambitions of 'joined up' service delivery, and whether jurisdictional boundaries are evident in the online world. In examining these topics, this paper seeks to provide an empirical and conceptual contribution to understanding 21 st government and service delivery.

- by Paul Henman
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- Computational Sociology, Social Policy, E Government, Social Network Analysis (SNA)