El artículo toma como hilo la participación de Félix Weil, durante la década del 30, en el Colegio Libre de Estudios Superiores y su revista Cursos y Conferencias. Analiza las discusiones propuestas por los tres cursos que dictó Weil a partir de su vinculación con el Partido Socialista Independiente y el Ministerio de Hacienda, con la circulación del materialismo dialéctico y con la construcción de un frente cultural antifascista. Ello permite rescatar una primera recepción argentina del Instituto de Investigación Social en Frankfurt anclada en la economía marxista.
1789-, Labor in politics. Political activity of the working class
Nowadays, people in the modern world communicate with their friends, relatives, and colleagues through the internet. Persons/nodes and communication/edges among them form a network. Social media networks are a type of network where people share their views with the community. There are several models that capture human behavior, such as a reaction to the information received from friends or relatives. The two fundamental models of information diffusion widely discussed in the social networks are the Independent Cascade Model and the Linear Threshold Model. Liu et al. [1] propose a variant of the linear threshold model in their paper title User-driven competitive influence Maximization(UDCIM) in social networks. Authors try to simulate human behavior where they do not make a decision immediately after being influenced, but take a pause for a while, and then they make a final decision. They propose the heuristic algorithms and prove the approximation factor under community constraints( The seed vertices belong to an identical community). Even finding the community is itself an NP-hard problem. In this article, we extend the existing work with algorithms and LP-formation of the problem. We also implement and test the LP-formulated equations on small datasets by using the Gurobi Solver [2]. We furthermore propose one heuristic and one genetic algorithm. The extensive experimentation is carried out on medium to large datasets, and the outcomes of both algorithms are plotted in the results and discussion section.
Productive software engineering teams require effective communication and balanced contributions between team members. However, teams are often ineffective at these skills, which is detrimental to project success. Project-based university courses are an opportunity for students to practise these skills, but we have yet to establish how we can guide students towards improving their communication and coordination. We aim to develop project management tool features, informed by social network analysis, that nudge students in software engineering group projects towards beneficial behaviours. To do this, we will first evaluate the suitability of social network analysis techniques for identifying areas of improvement in teams' communication. Then, we will develop features in a project management tool that aid students in identifying and addressing these areas of improvement, and evaluate them in the context of a software engineering group project.
Arman Isajanyan, Artur Shatveryan, David Kocharyan
et al.
Social reward as a form of community recognition provides a strong source of motivation for users of online platforms to engage and contribute with content. The recent progress of text-conditioned image synthesis has ushered in a collaborative era where AI empowers users to craft original visual artworks seeking community validation. Nevertheless, assessing these models in the context of collective community preference introduces distinct challenges. Existing evaluation methods predominantly center on limited size user studies guided by image quality and prompt alignment. This work pioneers a paradigm shift, unveiling Social Reward - an innovative reward modeling framework that leverages implicit feedback from social network users engaged in creative editing of generated images. We embark on an extensive journey of dataset curation and refinement, drawing from Picsart: an online visual creation and editing platform, yielding a first million-user-scale dataset of implicit human preferences for user-generated visual art named Picsart Image-Social. Our analysis exposes the shortcomings of current metrics in modeling community creative preference of text-to-image models' outputs, compelling us to introduce a novel predictive model explicitly tailored to address these limitations. Rigorous quantitative experiments and user study show that our Social Reward model aligns better with social popularity than existing metrics. Furthermore, we utilize Social Reward to fine-tune text-to-image models, yielding images that are more favored by not only Social Reward, but also other established metrics. These findings highlight the relevance and effectiveness of Social Reward in assessing community appreciation for AI-generated artworks, establishing a closer alignment with users' creative goals: creating popular visual art. Codes can be accessed at https://github.com/Picsart-AI-Research/Social-Reward
Yuwei Chuai, Anastasia Sergeeva, Gabriele Lenzini
et al.
Displaying community fact-checks is a promising approach to reduce engagement with misinformation on social media. However, how users respond to misleading content emotionally after community fact-checks are displayed on posts is unclear. Here, we employ quasi-experimental methods to causally analyze changes in sentiments and (moral) emotions in replies to misleading posts following the display of community fact-checks. Our evaluation is based on a large-scale panel dataset comprising N=2,225,260 replies across 1841 source posts from X's Community Notes platform. We find that informing users about falsehoods through community fact-checks significantly increases negativity (by 7.3%), anger (by 13.2%), disgust (by 4.7%), and moral outrage (by 16.0%) in the corresponding replies. These results indicate that users perceive spreading misinformation as a violation of social norms and that those who spread misinformation should expect negative reactions once their content is debunked. We derive important implications for the design of community-based fact-checking systems.
Azza Bouleimen, Nicolò Pagan, Stefano Cresci
et al.
Several one-fits-all intervention policies were introduced by the Online Social Networks (OSNs) platforms to mitigate potential harms. Nevertheless, some studies showed the limited effectiveness of these approaches. An alternative to this would be a user-centered design of intervention policies. In this context, we study the susceptibility of users to undesired behavior in communities on OSNs. In particular, we explore their reaction to specific events. Our study shows that communities develop different undesired behavior patterns in reaction to specific events. These events can significantly alter the behavior of the community and invert the dynamics of behavior within the whole network. Our findings stress out the importance of understanding the reasons behind the changes in users' reactions and highlights the need of fine-tuning the research to the individual's level. It paves the way towards building better OSNs' intervention strategies centered on the user.
Due to the recent development of data analysis techniques, technologies for detecting communities through information expressed in social networks have been developed. Although it has several advantages, including the ability to effectively share recommended items through an estimated community, it may cause personal privacy issues. Therefore, recently, the problem of hiding the real community well is being studied at the same time. As an example, Mittal \etal, proposed an algorithm called NEURAL that can hide this community well based on a metric called permanence. Based on this, in this study, we propose a Reverse NEURAL (R-NEURAL) algorithm that restores the community as well as the original graph structure using permanence. The proposed algorithm includes a method for well restoring not only the community hidden by the NEURAL algorithm but also the original graph structure modified by recovered edges. We conduct experiments on real-world graphs and found that the proposed algorithm recovers well the hidden community as well as the graph structure.
In light of the growing number of user privacy violations in centralized social networks, the need to define effective platforms for decentralized online social networks (DOSNs) is deeply felt. Interesting solutions have been proposed in the past, which own the necessary mechanisms to allow users keeping control over their personal information and setting the rules to regulate the access of other users. Unfortunately, the effectiveness of this type of solutions is severely reduced by the fact that different user communities with a shared interest could be disconnected/separated from each other. This translates into a reduced ability in effectively spreading data of common interest towards all interested users, as it currently happens in centralized social networks. In order to overcome the cited limitation, this paper proposes a disruptive approach, which exploits the availability of a new class of Internet of Things (IoT) devices with autonomous social behaviors and cognitive abilities. Such devices can be leveraged as friendship intermediaries between devices' owners who are connected to a DOSN platform and share the same interest. We will demonstrate that clear advantages can be achieved in terms of increased percentage of Interested Reachable Nodes (a specific measure of Delivery Ratio) in distributed social networks among humans, when enhanced with so called Mediator Objects adhering to the well-known social IoT (SIoT) paradigm.
Corrado Monti, Luca Maria Aiello, Gianmarco De Francisci Morales
et al.
Which messages are more effective at inducing a change of opinion in the listener? We approach this question within the frame of Habermas' theory of communicative action, which posits that the illocutionary intent of the message (its pragmatic meaning) is the key. Thanks to recent advances in natural language processing, we are able to operationalize this theory by extracting the latent social dimensions of a message, namely archetypes of social intent of language, that come from social exchange theory. We identify key ingredients to opinion change by looking at more than 46k posts and more than 3.5M comments on Reddit's r/ChangeMyView, a debate forum where people try to change each other's opinion and explicitly mark opinion-changing comments with a special flag called "delta". Comments that express no intent are about 77% less likely to change the mind of the recipient, compared to comments that convey at least one social dimension. Among the various social dimensions, the ones that are most likely to produce an opinion change are knowledge, similarity, and trust, which resonates with Habermas' theory of communicative action. We also find other new important dimensions, such as appeals to power or empathetic expressions of support. Finally, in line with theories of constructive conflict, yet contrary to the popular characterization of conflict as the bane of modern social media, our findings show that voicing conflict in the context of a structured public debate can promote integration, especially when it is used to counter another conflictive stance. By leveraging recent advances in natural language processing, our work provides an empirical framework for Habermas' theory, finds concrete examples of its effects in the wild, and suggests its possible extension with a more faceted understanding of intent interpreted as social dimensions of language.
The document provides the proof to properties of community evolution indices including community split and shrink in paper: Liang Wang, Ying Li, Jierui Zhang, and Xianping Tao. 2022. Quantifying Community Evolution in Developer Social Networks. In Proceedings of the30th ACM Joint European Software Engineering Conference and Symposiumon the Foundations of Software Engineering (ESEC/FSE 22), November 14 - 18, 2022, Singapore, Singapore. ACM, New York, NY, USA, 12 pages. Proof to properties of community merge and expand is similar.
El objetivo de este trabajo es demostrar que la recepción de Alain Badiou en Argentina tuvo un carácter temprano y político. Para ello, analizaremos la revista Acontecimiento, que durante veinticinco años llevó a cabo una lectura de la realidad argentina y latinoamericana a través de tesis y conceptos provenientes de la obra del filósofo francés. En la primera mitad de la década de 1990 la revista procesará el derrumbe del socialismo real y la imposición de una gramática política democrática. En la segunda mitad de la década de 1990, diferentes experiencias políticas serán caracterizadas como una nueva secuencia política desplegada a distancia de los partidos y el Estado.
1789-, Labor in politics. Political activity of the working class
Kielland-ulykken, eller katastrofen, i 1980 er den største industrielle ulykken vi har hatt i Norge. Kantringen av plattformen er også den største maritime ulykken som har vært i Norge etter krigen og den som utløste den største internasjonale redningsaksjonen vi har hatt i Nordsjøen. Totalt døde det 123 menn i ulykken, 89 overlevde. Av de omkomne ble 30 aldri funnet. Ulykken avslørte mangelfullt redningsutstyr, manglende tilgjengelighet på sikkerhetsutstyr, svikt i beredskapen og mangelfull sikkerhetsopplæring. Men den viste også betydningen av god trening, vurderingsevne og profesjonalitet både blant redningsmannskapet og de som var om bord på Kielland. I artikkelen diskuterer vi betydningen av egeninnsatsen og samarbeidet mellom de som var om bord på Kielland og naboplattformen Edda. Det var en innsats der samarbeid var avgjørende viktig for at mange overlevde, men som også førte til at noen omkom under forsøk på å redde andre. Vi beskriver redningsaksjonen med utgangspunkt i erfaringer fra dem som var med på ulykken. Vi utdyper egeninnsatsen og samarbeidet, og analyserer mekanismene bak denne samhandlingen ut fra tenking rundt solidaritet og samhold. Informantene og perspektivet er fra de som overlevde ulykken, de som var med på redningsaksjonen og de som var vitner til den fra luften og fra skipene.
Egeninnsatsen var avgjørende for at den redningskapasiteten som kom til med helikopter og skip hadde noen å redde. Det var helt avgjørende med samholdet og samarbeidet mellom de som havnet i ulykken. Den solidariteten som var mellom arbeiderne, var kraften i arbeiderfellesskapet og gjorde at 89 overlevde mot alle odds.
Socialism. Communism. Anarchism, Economic history and conditions
El texto se dedica a la historia de la Oposición de Izquierda en la Argentina, desde sus orígenes hasta 1933, año en que se conformó como corriente política y organizativa separada de la Comintern. El autor examina esta experiencia en su propia especificidad y en cotejo con el devenir del campo comunista, antes de la constitución del trotskismo como espacio identitario. Lo hace a partir de fuentes primarias antes inexploradas.
1789-, Labor in politics. Political activity of the working class
En el marco de los debates académicos y políticos actuales, en este artículo proponemos abordar un tema que ha estado presente en el campo de las discusiones, desde distintos enfoques y perspectivas: la militancia sindical de las mujeres trabajadoras. A partir de la revisión de la bibliografía producida en Argentina en los últimos años, nos centramos en el cruce entre militancia, género y clase con el propósito de contribuir a mapear algunas de las principales discusiones existentes en el campo de la sociología.
1789-, Labor in politics. Political activity of the working class
The novel COVID-19 pandemic is a current, major global health threat. Up till now, there is no fully approved pharmacological treatment or a vaccine. In this study, simple mathematical models were employed to examine the dynamics of transmission and control of COVID-19 taking into consideration social distancing and community awareness. Both situations of homogeneous and nonhomogeneous population were considered. Based on the calculations, a sufficient degree of social distancing based on its reproductive ratio is found to be effective in controlling COVID-19, even in the absence of a vaccine. With a vaccine, social distancing minimizes the sufficient vaccination rate to control the disease. Community awareness also has a great impact in eradicating the virus transmission. The model is simulated on small-world networks and the role of social distancing in controlling the infection is explained.
Media organisations are essential communication stakeholders in social media disaster communication during extreme events. They perform gatekeeper and amplification roles which are crucial for collective sense-making processes. In that capacity, media organisations distribute information through social media, use it as a source of information, and share such information across different channels. Yet, little is known about the role of media organisations on social media as supposed sense-givers to effectively support the creation of mutual sense. This study investigates the communication strategies of media organisations in extreme events. A Twitter dataset consisting of 9,414,463 postings was collected during Hurricane Harvey in 2017. Social network and content analysis methods were applied to identify media communication approaches. Three different sense-giving strategies could be identified: retweeting of local in-house outlets; bound amplification of messages of individual to the organisation associated journalists; and open message amplification.
Development strategies of International Financial Institutions (IFIs), such as education strategies of the World Bank, advance globalization in part by promoting networks as organizational forms in public services and wider society. Networks are inherently decentralizing and are becoming the dominant organizational form due to advances in Information and Communication Technologies (ICT). The work of Karl Marx (interpreted through David Harvey), Manuel Castells, and Gilles Deleuze and Felix Guattari provide new insights into the use of ICT and networks as a social organizational form. Technology does not determine society, but reveals our relations to nature, production, and reproduction, our social relations, and our mental conceptions. These relations are dialectic in the Marxian sense that we cannot change the world around us without also changing ourselves. World Bank education strategies advance a networked type of education system, and impose a new form of discipline, to facilitate the emergence of a knowledge economy. However, the World Bank does not include our relation to nature in these strategies, and the strategies lack detail concerning modes of production and reproduction – essential to knowing why education is necessary. A more comprehensive understanding of the network form and ICT can contribute to critiques of development discourses in education reform and modes of being in the world.