Hasil untuk "Socialism. Communism. Anarchism"

Yingnan Xu, Shuangshuang Chu

Community discovery is a central problem in the analysis of dynamic social networks. Traditional community discovery methods mainly focus on the formation and dissolution of links between nodes, and therefore often fail to capture the richer spatial structure and temporal dependency underlying network evolution. To address this limitation, we propose STEC-Net, a spatiotemporal graph neural framework for community discovery in dynamic social networks. STEC-Net integrates spatial structure and temporal dynamics within a unified embedding architecture. First, Graph Convolutional Networks (GCNs) are used to learn snapshot-level node representations from network topology. To adapt the spatial encoder to structural evolution, a GRU-based weight evolution mechanism is introduced to update the GCN parameters over time. Then, a second Gated Recurrent Unit (GRU) is employed to model temporal dependencies across snapshot embeddings and to learn spatiotemporal node representations. Finally, a Self-Organizing Map (SOM) is applied to the learned embeddings to cluster nodes and infer their community affiliations. Experiments on four types of dynamic networks show that STEC-Net consistently outperforms traditional community discovery methods in terms of purity, normalized mutual information, homogeneity, and completeness. These results demonstrate that STEC-Net can effectively uncover evolving community structures in dynamic social networks.

Eurelino Coelho

La Organização Revolucionária Marxista Política Operária (Polop) es vista, frecuentemente, como pionera en la superación teórica del estalinismo y en la renovación del marxismo en Brasil, el punto de partida de la “nueva izquierda” brasileña. Este artículo contextualiza y expone, de modo sintético, la trayectoria de Polop y recupera el proceso de elaboración de sus tesis consideradas innovadoras. Al examinar su trayectoria, por un lado, relativizamos la idea de su carácter teórico pionero y, por otra parte, resaltamos aspectos innovadores en la praxis de la organización que aún han sido poco estudiados.

Jacob Blumenfeld

A los 25 años, en 1923, el argentino Félix Weil fundó el Institut für Sozialforschung con una donación de su padre, el comerciante de cereales Hermann Weil. Weil fue alumno de Robert Wilbrandt, profesor de la Universidad de Tubinga, que formó parte de la Comisión de Socialización tras la revolución alemana en 1918-1919. Wilbrandt animó a Weil a convertir un ensayo suyo sobre la socialización en una disertación, que finalmente se publicó en 1921. El texto de Weil, Socialización, nunca se ha traducido, y casi nunca se ha comentado. En este artículo, hablaré del texto, mostrando el contexto en el que surgió: el debate sobre la socialización entre 1918 y 1921 en Alemania.

Mohammad Rashidujjaman Rifat, Dipto Das, Arpon Podder et al.

Despite significant research on online harm, polarization, public deliberation, and justice, CSCW still lacks a comprehensive understanding of the experiences of religious minorities, particularly in relation to fear, as prominently evident in our study. Gaining faith-sensitive insights into the expression, participation, and inter-religious interactions on social media can contribute to CSCW's literature on online safety and interfaith communication. In pursuit of this goal, we conducted a six-month-long, interview-based study with the Hindu, Buddhist, and Indigenous communities in Bangladesh. Our study draws on an extensive body of research encompassing the spiral of silence, the cultural politics of fear, and communication accommodation to examine how social media use by religious minorities is influenced by fear, which is associated with social conformity, misinformation, stigma, stereotypes, and South Asian postcolonial memory. Moreover, we engage with scholarly perspectives from religious studies, justice, and South Asian violence and offer important critical insights and design lessons for the CSCW literature on public deliberation, justice, and interfaith communication.

Amirhossein Dezhboro, Jose Emmanuel Ramirez-Marquez, Aleksandra Krstikj

This research presents a framework for analyzing the dynamics of online communities in social media platforms, utilizing a temporal fusion of text and network data. By combining text classification and dynamic social network analysis, we uncover mechanisms driving community formation and evolution, revealing the influence of real-world events. We introduced fourteen key elements based on social science theories to evaluate social media dynamics, validating our framework through a case study of Twitter data during major U.S. events in 2020. Our analysis centers on discrimination discourse, identifying sexism, racism, xenophobia, ableism, homophobia, and religious intolerance as main fragments. Results demonstrate rapid community emergence and dissolution cycles representative of discourse fragments. We reveal how real-world circumstances impact discourse dominance and how social media contributes to echo chamber formation and societal polarization. Our comprehensive approach provides insights into discourse fragmentation, opinion dynamics, and structural aspects of online communities, offering a methodology for understanding the complex interplay between online interactions and societal trends.

Omar Hammad, Md Rezwanur Rahman, Gopala Krishna Vasanth Kanugo et al.

Frequent disruptions like highway constructions are common now-a-days, often impacting environmental justice communities (communities with low socio-economic status with disproportionately high and adverse human health and environmental effects) that live nearby. Based on our interactions via focus groups with the members of four environmental justice communities impacted by a major highway construction, a common concern is a sense of uncertainty about project activities and loss of social connectedness, leading to increased stress, depression, anxiety and diminished well-being. This paper addresses this concern by developing a localized social media system called PureConnect with a goal to raise the level of awareness about the project and increase social connectedness among the community members. PureConnect has been designed using active engagement with four environmental justice communities affected by a major highway construction. It has been deployed in the real world among the members of the four environmental justice communities, and a detailed analysis of the data collected from this deployment as well as surveys show that PureConnect is potentially useful in improving community members' well-being and the members appreciate the functionalities it provides.

Jonathan Palla

Desde la década de 1920 maduraron conflictos en las relaciones que estructuraban el mercado del boxeo profesional. Estas tensiones se expresaron en imágenes de explotación laboral derivadas de la vulnerabilidad de los jóvenes boxeadores en duras condiciones de trabajo. Durante la década siguiente, los contratos entre promotor y el boxeador fueron vistos como símbolo de inmoralidad en la explotación laboral. Atravesado por una larga y conflictiva coexistencia entre esas dos claves de explicación, la moral y la del trabajo, el boxeo profesional también participó de los impulsos organizativos y sindicales de la clase trabajadora durante la postguerra, mostrando que los objetivos de movilidad ascendente convivieron con otras formas de significar el trabajo en el espectáculo deportivo.

Leandro Molinaro

Presentación

Moritz Pilarski, Kirill Solovev, Nicolas Pröllochs

Deploying links to fact-checking websites (so-called "snoping") is a common intervention that can be used by social media users to refute misleading claims. However, its real-world effect may be limited as it suffers from low visibility and distrust towards professional fact-checkers. As a remedy, Twitter launched its community-based fact-checking system Community Notes on which fact-checks are carried out by actual Twitter users and directly shown on the fact-checked tweets. Yet, an understanding of how fact-checking via Community Notes differs from snoping is absent. In this study, we analyze differences in how contributors to Community Notes and Snopers select their targets when fact-checking social media posts. For this purpose, we analyze two unique datasets from Twitter: (a) 25,912 community-created fact-checks from Twitter's Community Notes platform; and (b) 52,505 "snopes" that debunk tweets via fact-checking replies linking to professional fact-checking websites. We find that Notes contributors and Snopers focus on different targets when fact-checking social media content. For instance, Notes contributors tend to fact-check posts from larger accounts with higher social influence and are relatively less likely to endorse/emphasize the accuracy of not misleading posts. Fact-checking targets of Notes contributors and Snopers rarely overlap; however, those overlapping exhibit a high level of agreement in the fact-checking assessment. Moreover, we demonstrate that Snopers fact-check social media posts at a higher speed. Altogether, our findings imply that different fact-checking approaches -- carried out on the same social media platform -- can result in vastly different social media posts getting fact-checked. This has important implications for future research on misinformation, which should not rely on a single fact-checking approach when compiling misinformation datasets.

Yanming Wan, Jiayuan Mao, Joshua B. Tenenbaum

We introduce HandMeThat, a benchmark for a holistic evaluation of instruction understanding and following in physical and social environments. While previous datasets primarily focused on language grounding and planning, HandMeThat considers the resolution of human instructions with ambiguities based on the physical (object states and relations) and social (human actions and goals) information. HandMeThat contains 10,000 episodes of human-robot interactions. In each episode, the robot first observes a trajectory of human actions towards her internal goal. Next, the robot receives a human instruction and should take actions to accomplish the subgoal set through the instruction. In this paper, we present a textual interface for our benchmark, where the robot interacts with a virtual environment through textual commands. We evaluate several baseline models on HandMeThat, and show that both offline and online reinforcement learning algorithms perform poorly on HandMeThat, suggesting significant room for future work on physical and social human-robot communications and interactions.

Khaled Kassem, Alia Saad

Socially Assistive Robots (SARs) are robots that are designed to replicate the role of a caregiver, coach, or teacher, providing emotional, cognitive, and social cues to support a specific group. SARs are becoming increasingly prevalent, especially in elderly care. Effective communication, both explicit and implicit, is a critical aspect of human-robot interaction involving SARs. Intent communication is necessary for SARs to engage in effective communication with humans. Biometrics can provide crucial information about a person's identity or emotions. By linking these biometric signals to the communication of intent, SARs can gain a profound understanding of their users and tailor their interactions accordingly. The development of reliable and robust biometric sensing and analysis systems is critical to the success of SARs. In this work, we focus on four different aspects to evaluate the communication of intent involving SARs, existing works, and our outlook on future works and applications.

Zhilong Chen, Hancheng Cao, Xiaochong Lan et al.

The disadvantaged population is often underserved and marginalized in technology engagement: prior works show they are generally more reluctant and experience more barriers in adopting and engaging with mainstream technology. Here, we contribute to the HCI4D and ICTD literature through a novel "counter" case study on Chinese social commerce (e.g., Pinduoduo), which 1) first prospers among the traditionally underserved community from developing regions ahead of the more technologically advantaged communities, and 2) has been heavily engaged by this community. Through 12 in-depth interviews with social commerce users from the traditionally underserved community in Chinese developing regions, we demonstrate how social commerce, acting as a "counter", brings online the traditional offline socioeconomic lives the community has lived for ages, fits into the community's social, cultural, and economic context, and thus effectively promotes technology inclusivity. Our work provides novel insights and implications for building inclusive technology for the "next billion" population.

Stephany Rajeh, Marinette Savonnet, Eric Leclercq et al.

Identifying key nodes is crucial for accelerating or impeding dynamic spreading in a network. Community-aware centrality measures tackle this problem by exploiting the community structure of a network. Although there is a growing trend to design new community-aware centrality measures, there is no systematic investigation of the proposed measures' effectiveness. This study performs an extensive comparative evaluation of prominent community-aware centrality measures using the Susceptible-Infected-Recovered (SIR) model on real-world online social networks. Overall, results show that K-shell with Community and Community-based Centrality measures are the most accurate in identifying influential nodes under a single-spreader problem. Additionally, the epidemic transmission rate doesn't significantly affect the behavior of the community-aware centrality measures.

Jie Gao, Junping Du, Yingxia Shao et al.

Shared travel has gradually become one of the hot topics discussed on social networking platforms such as Micro Blog. In a timely manner, deeper network community detection on the evaluation content of shared travel in social networks can effectively conduct research and analysis on the public opinion orientation related to shared travel, which has great application prospects. The existing community detection algorithms generally measure the similarity of nodes in the network from the perspective of spatial distance. This paper proposes a Community detection algorithm based on Textual content Similarity and sentimental Tendency (CTST), considering the network structure and node attributes at the same time. The content similarity and sentimental tendency of network community users are taken as node attributes, and on this basis, an undirected weighted network is constructed for community detection. This paper conducts experiments with actual data and analyzes the experimental results. It is found that the modularity of the community detection results is high and the effect is good.

Johanne Bergkvist

Gustavo Oliveira, Agnaldo de Souza Batista, Michele Nogueira et al.

The evolution of the Internet of Things (IoT) has increased the connection of personal devices, mainly taking into account the habits and behavior of their owners. These environments demand access control mechanisms to protect them against intruders, like Sybil attacks. that can compromise data privacy or disrupt the network operation. The Social IoT paradigm enables access control systems to aggregate community context and sociability information from devices to enhance robustness and security. This work introduces the ELECTRON mechanism to control access in IoT networks based on social trust between devices to protect the network from Sybil attackers. ELECTRON groups IoT devices into communities by their social similarity and evaluates their social trust, strengthening the reliability between legitimate devices and their resilience against the interaction of Sybil attackers. NS-3 Simulations show the ELECTRON performance under Sybil attacks on several IoT communities so that it has gotten to detect more than 90% of attackers in a scenario with 150 nodes into offices, schools, gyms, and~parks communities, and in other scenarios for same communities it achieved around of 90\% of detection. Furthermore, it provided high accuracy, over 90-95%, and false positive rates closer to zero.

Maximiliano Basilio Cladakis

El presente estudio tiene por objetivo abordar la relación entre filosofía, historia y marxismo desde el debate entre Jean Paul Sartre y Maurice Merleau-Ponty. Dicha relación excede el campo teórico para extenderse sobre el campo histórico-político. Precisamente, para ambos autores la filosofía se da en un anudamiento con el mundo de la vida imposible de evitar. Con esta finalidad, trataremos el debate entre Sartre y Merleau-Ponty teniendo en cuenta sus miradas y posicionamientos con respecto a los acontecimientos que hicieron a su contemporaneidad.

Dennis Klinkhammer

Communication on social media platforms is not only culturally and politically relevant, it is also increasingly widespread across societies. Users not only communicate via social media platforms, but also search specifically for information, disseminate it or post information themselves. However, fake news, hate speech and even radicalizing elements are part of this modern form of communication: Sometimes with far-reaching effects on individuals and societies. A basic understanding of these mechanisms and communication patterns could help to counteract negative forms of communication, e.g. bullying among children or extreme political points of view. To this end, a method will be presented in order to break down the underlying communication patterns, to trace individual users and to inspect their comments and range on social media platforms; Or to contrast them later on via qualitative research. This approeach can identify particularly active users with an accuracy of 100 percent, if the framing social networks as well as the topics are taken into account. However, methodological as well as counteracting approaches must be even more dynamic and flexible to ensure sensitivity and specifity regarding users who spread hate speech, fake news and radicalizing elements.

Xihui Chen, Sjouke Mauw, Yunior Ramírez-Cruz

We present a novel method for publishing differentially private synthetic attributed graphs. Unlike preceding approaches, our method is able to preserve the community structure of the original graph without sacrificing the ability to capture global structural properties. Our proposal relies on C-AGM, a new community-preserving generative model for attributed graphs. We equip C-AGM with efficient methods for attributed graph sampling and parameter estimation. For the latter, we introduce differentially private computation methods, which allow us to release community-preserving synthetic attributed social graphs with a strong formal privacy guarantee. Through comprehensive experiments, we show that our new model outperforms its most relevant counterparts in synthesising differentially private attributed social graphs that preserve the community structure of the original graph, as well as degree sequences and clustering coefficients.

Nerina Visacovsky

Este trabajo da cuenta de los orígenes y el devenir del movimiento judeo-progresista en el Río de la Plata entre la Primera Guerra Mundial y el inicio de la Guerra Fría. Frente al avance del fascismo y el antisemitismo, en los años 30, se constituyó internacionalmente el Idisher Cultur Farband (ICUF), liderado por intelectuales judíos comunistas de habla ídish. Vistas en conjunto, las experiencias institucionales reflejan la construcción de una identidad tanto étnica como política. En tanto “judías” se proponían transmitir el patrimonio cultural idishista, pero en tanto “progresistas” postulaban su anhelo de integración a un socialismo universalista. La investigación demostró que esa identidad se modeló en un campo de tensiones entre la pertenencia étnica, los lineamientos del Partido Comunista y la aspiración colectiva de integración nacional, argentina y uruguaya.