CulSim: A simulator of emergence and resilience of cultural diversity

CulSim is an agent-based computer simulation software that allows further exploration of influential and recent models of emergence of cultural groups grounded in sociological theories. CulSim provides a collection of tools to analyze resilience of cultural diversity when events affect agents, institutions or global parameters of the simulations; upon combination, events can be used to approximate historical circumstances. The software provides a graphical and text-based user interface, and so makes this agent-based modeling methodology accessible to a variety of users from different research fields

Rediseño, implementación y validación de un proceso de elaboración de comprimidos recubiertos de ibuprofeno.

Tesis (Químico Farmacéutico)El proceso de elaboración de Ibuprofeno en comprimidos recubiertos de 400 mg, se realizó durante años mediante granulación vía húmeda, presentando diversos inconvenientes que afectaban la productividad. Estos inconvenientes se refieren a la dificultad de obtener comprimidos dentro de los rangos de especificación del producto farmacéutico, largo tiempo de secado del granulado en los hornos y adherencia del granulado a los punzones de la comprimidora. Por la razón señalada se rediseñó, implementó y validó el proceso de elaboración de este producto farmacéutico. La nueva propuesta fue fabricar Ibuprofeno en comprimidos recubiertos mediante compresión directa, a partir de una nueva formulación basada en la fórmula cualitativa utilizada en el método anterior, pero incorporando las modificaciones necesarias para favorecer el nuevo proceso; del mismo modo, se adaptó el método de fabricación, eliminándose las etapas de granulación húmeda y secado en los hornos, manteniéndose las etapas de tamizado, mezclado, compresión y recubrimiento. Para llevar a cabo estas modificaciones, fue necesario realizar dos controles de cambios. Consecutivamente, se elaboró un lote de prueba de tamaño comercial mediante compresión directa, en el que se evaluaron los comprimidos recubiertos por medio de los correspondientes controles en proceso, realizados tanto en la etapa de compresión como en la etapa de recubrimiento. Todos los controles realizados durante la elaboración del lote de prueba, obtuvieron resultados dentro de los rangos de especificación establecidos; por lo tanto, se implementó el proceso de elaboración mediante compresión directa y se procedió a su validación, utilizando 5 lotes consecutivos, estableciéndose previamente sus puntos críticos y parámetros a cuantificar. Finalmente, se evaluó la capacidad del proceso productivo para obtener comprimidos recubiertos dentro de sus especificaciones

Nobility-targeting raids among the Classic Maya: Cooperation in scale-free networks persists under tournament attack when population size fluctuates

Cooperation in scale-free networks has proven to be very robust against removal of randomly selected nodes (error) but highly sensitive to removal of the most connected nodes (attack). In this paper we analyze two comparable types of node removal in which the removal selection is based on tournaments where the fittest (raids) or the least fit (battles) nodes are chosen. We associate the two removals to two types of Maya warfare offences during the Classic period. During this period of at least 500 years, political leaders were able to sustain social order in spite of attack-like offences to their social networks. We present a computational model with a population fluctuation mechanism that operates under an evolutionary game theoretic approach using the Prisoner's Dilemma as a metaphor of cooperation. We find that paradoxically battles are able to uphold cooperation under moderate levels of raids, although raids do have a strong impact on the network structure. We infer that cooperation does not depend as much on the structure as it does on the underlying mechanism that allows the network to readjust. We relate the results to the Maya Classic period, concluding that Mayan warfare by itself cannot entirely explain the Maya political collapse without appealing to other factors that increased the pressures against cooperation

Search engine effects on news consumption: Ranking and representativeness outweigh familiarity in news selection

While individuals' trust in search engine results is well-supported, little is known about their preferences when selecting news. We use web-tracked behavioral data across a 2-month period (280 participants) and we analyze three competing factors, two algorithmic (ranking and representativeness) and one psychological (familiarity), that could influence the selection of search results. We use news engagement as a proxy for familiarity and investigate news articles presented on Google search pages (n = 1221). We find a significant effect of algorithmic factors but not of familiarity. We find that ranking plays a lesser role for news compared to non-news, suggesting a more careful decision-making process. We confirm that Google Search drives individuals to unfamiliar sources, and find that it increases the diversity of the political audience of news sources. We tackle the challenge of measuring social science theories in contexts shaped by algorithms, demonstrating their leverage over the behaviors of individuals

Do Athletes Imagine Being the Best, or Crossing the Finish Line First? A Mixed Methods Analysis of Construal Levels in Elite Athletes' Spontaneous Imagery

The purpose of this article is to illustrate data transformation in a mixed methods research phenomenological study, investigating how athletes use concrete and abstract spontaneous imagery in and around competition. To achieve this, we combined the application of co-occurring codes and numerical transformation in a novel way. A thematic analysis of qualitative interviews with 12 elite athletes identified concrete imagery to focus on strategy generation, error correction, technique, and preparation, and abstract imagery to focus on desirability, symbolic and verbal representations, and regulation of affect, arousal, and mastery. Statistical analysis identified that subjective effectiveness of imagery significantly differed for sport type (reactive/static) and competition times. Researchers wishing to apply statistical analyses to qualitative data are encouraged to employ our methodology

Auditing the representation of migrants in image web search results

Search engines serve as information gatekeepers on a multitude of topics that are prone to gender, ethnicity, and race misrepresentations. In this paper, we specifically look at the image search representation of migrant population groups that are often subjected to discrimination and biased representation in mainstream media, increasingly so with the rise of right-wing populist actors in the Western countries. Using multiple (n = 200) virtual agents to simulate human browsing behavior in a controlled environment, we collect image search results related to various terms referring to migrants (e.g., expats, immigrants, and refugees, seven queries in English and German used in total) from the six most popular search engines. Then, with the aid of manual coding, we investigate which features are used to represent these groups and whether the representations are subjected to bias. Our findings indicate that search engines reproduce ethnic and gender biases common for mainstream media representations of different subgroups of migrant population. For instance, migrant representations tend to be highly racialized, and female migrants as well as migrants at work tend to be underrepresented in the results. Our findings highlight the need for further algorithmic impact auditing studies in the context of representation of potentially vulnerable groups in web search results

Scaling up search engine audits: Practical insights for algorithm auditing

Algorithm audits have increased in recent years due to a growing need to independently assess the performance of automatically curated services that process, filter and rank the large and dynamic amount of information available on the Internet. Among several methodologies to perform such audits, virtual agents stand out because they offer the ability to perform systematic experiments, simulating human behaviour without the associated costs of recruiting participants. Motivated by the importance of research transparency and replicability of results, this article focuses on the challenges of such an approach. It provides methodological details, recommendations, lessons learned and limitations based on our experience of setting up experiments for eight search engines (including main, news, image and video sections) with hundreds of virtual agents placed in different regions. We demonstrate the successful performance of our research infrastructure across multiple data collections, with diverse experimental designs, and point to different changes and strategies that improve the quality of the method. We conclude that virtual agents are a promising venue for monitoring the performance of algorithms across long periods of time, and we hope that this article can serve as a basis for further research in this area

Memory, counter-memory and denialism: How search engines circulate information about the Holodomor-related memory wars

Search engines, such as Google or Yandex, shape social reality by informing their users about current and historical phenomena. However, there is little research on how search engines deal with contested memories, which are subjected to ontological conflicts known as memory wars. In this article, we investigate how search engines circulate information about memory wars related to the Holodomor, a mass famine caused by Soviet repressive politics in Ukraine in 1932-1933. For this aim, we conduct an agent-based audit of four search engines - Bing, DuckDuckGo, Google, and Yandex - and examine how their top search results represent the Holodomor and related memory wars. Our findings demonstrate that search engines prioritize interpretations of the Holodomor aligning with specific sides in the memory wars, thus becoming memory warriors themselves

Memory, counter-memory and denialism: How search engines circulate information about the Holodomor-related memory wars

Search engines, such as Google or Yandex, shape social reality by informing their users about current and historical phenomena. However, there is little research on how search engines deal with contested memories, which are subjected to ontological conflicts known as memory wars. In this article, we investigate how search engines circulate information about memory wars related to the Holodomor, a mass famine caused by Soviet repressive politics in Ukraine in 1932–1933. For this aim, we conduct an agent-based audit of four search engines—Bing, DuckDuckGo, Google, and Yandex—and examine how their top search results represent the Holodomor and related memory wars. Our findings demonstrate that search engines prioritize interpretations of the Holodomor aligning with specific sides in the memory wars, thus becoming memory warriors themselves

This is what a pandemic looks like: Visual framing of COVID-19 on search engines

In today's high-choice media environment, search engines play an integral role in informing individuals and societies about the latest events. The importance of search algorithms is even higher at the time of crisis, when users search for information to understand the causes and the consequences of the current situation and decide on their course of action. In our paper, we conduct a comparative audit of how different search engines prioritize visual information related to COVID-19 and what consequences it has for the representation of the pandemic. Using a virtual agent-based audit approach, we examine image search results for the term "coronavirus" in English, Russian and Chinese on five major search engines: Google, Yandex, Bing, Yahoo, and DuckDuckGo. Specifically, we focus on how image search results relate to generic news frames (e.g., the attribution of responsibility, human interest, and economics) used in relation to COVID-19 and how their visual composition varies between the search engines.Comment: 18 pages, 1 figure, 3 table