Evolving Heterogeneous And Subcultured Social Networks For Optimization Problem Solving In Cultural Algorithms

Cultural Algorithms are computational models of social evolution based upon principle of Cultural Evolution. A Cultural Algorithm are composed of a Belief Space consisting of a network of active and passive knowledge sources and a Population Space of agents. The agents are connected via a social fabric over which information used in agent problem solving is passed. The knowledge sources in the Belief Space compete with each other in order to influence the decision making of agents in the Population Space. Likewise, the problem solving experiences of agents in the Population Space are sent back to the Belief Space and used to update the knowledge sources there. It is a dual inheritance system in which both the Population and Belief spaces evolve in parallel over generations. A question of interest to those studying the emergence of social systems is the extent to which their organizational structure reflects the structures of the problems that are presented to them. In a recent study [Reynolds, Che, and Ali, 2010] used Cultural Algorithms as a framework in which to empirically address this and related questions. There, a problem generator based upon Langton\u27s model of complexity was used to produce multi-dimensional real-valued problem landscapes of varying complexities. Various homogeneous social networks were then tested against the range of problems to see whether certain homogeneous networks were better at distributing problem solving knowledge from the Belief Space to individuals in the population. The experiments suggested that different network structures worked better in the distribution of knowledge for some optimization problems than others. If this is the case, then in a situation where several different problems are presented to a group, they may wish to utilize more than one network to solve them. In this thesis, we first investigate the advantages of utilizing a heterogeneous network over a suite of different problems. We show that heterogeneous approaches begin to dominate homogeneous ones as the problem complexity increases. A second heterogeneous approach, sub-culutres, will be introduced by dividing the social fabric into smaller networks. The three different social fabrics (homogeneous, heterogeneous and Sub-Cultures) were then compared relative to a variety of benchmark landscapes of varying entropy, from static to chaotic. We show that as the number of independent processes that are involved in the production of a landscape increases, the more advantageous subcultures are in directing the population to a solution. We will support our results with t-test statistics and social fabric metrics performance analysis

Complex Organizations: A Cultural Analysis of a Christian College

The purpose of this study was to understand the emergent dynamics that shape the organizational culture of a faith-based college incorporating a comprehensive network approach. The study adapted Martin\u27s (2002) Three Perspective Theory of Culture utilizing the Dynamic Network Analysis methodology. To understand the cultural manifestations of the organization, several networks of beliefs and agent interactions were examined. The results demonstrated that religious values are deeply embedded in the institution and there is a rich diversity of beliefs within the institution and its subcultures. The role of resources was examined, and financial resources emerged as a crucial element that stresses the operational culture. These findings combined to identify the emergent dichotomies related to ideological and operational cultural manifestations and how they interact together. Additionally, there were two findings that supported Complexity Leadership Theory (CLT). The first finding was that while organizational learning did occur within homogenous subcultures, greater organizational learning was demonstrated when the subcultures were brought together. This finding supported the premise of CLT, which suggests that a diversity of perspectives foster enhanced organizational learning. The second finding supported CLT through identification of clusters of employees utilizing common resources, tasks, and knowledge sets. The implication is for the organization to create bottom-up approaches that interact with existing top-down structures which would enable organizational learning, knowledge development, and problem-solving

Affect Lexicon Induction For the Github Subculture Using Distributed Word Representations

Sentiments and emotions play essential roles in small group interactions, especially in self-organized collaborative groups. Many people view sentiments as universal constructs; however, cultural differences exist in some aspects of sentiments. Understanding the features of sentiment space in small group cultures provides essential insights into the dynamics of self-organized collaborations. However, due to the limit of carefully human annotated data, it is hard to describe sentimental divergences across cultures. In this thesis, we present a new approach to inspect cultural differences on the level of sentiments and compare subculture with the general social environment. We use Github, a collaborative software development network, as an example of self-organized subculture. First, we train word embeddings on large corpora and do embedding alignment using linear transformation method. Then we model finer-grained human sentiment in the Evaluation- Potency-Activity (EPA) space and extend subculture EPA lexicon with two-dense-layered neural networks. Finally, we apply Long Short-Term Memory (LSTM) network to analyze the identities’ sentiments triggered by event-based sentences. We evaluate the predicted EPA lexicon for Github community using a recently collected dataset, and the result proves our approach could capture subtle changes in affective dimensions. Moreover, our induced sentiment lexicon shows individuals from two environments have different understandings to sentiment-related words and phrases but agree on nouns and adjectives. The sentiment features of “Github culture” could explain that people in self-organized groups tend to reduce personal sentiment to improve group collaboration

From cultural distance to cultural archetypes: an innovative approach to define cultural patterns

The purpose of this thesis is to present an innovative approach in the field of cultural studies, which emerges as the most recent and successful attempt to describe cultural patterns within and across countries. In 2015, cultural archetypes established as an alternative approach to the cultural distance construct, introduced by Geert Hofstede in the 1980s.ope

Artificial intelligence and the limits of the humanities

The complexity of cultures in the modern world is now beyond human comprehension. Cognitive sciences cast doubts on the traditional explanations based on mental models. The core subjects in humanities may lose their importance. Humanities have to adapt to the digital age. New, interdisciplinary branches of humanities emerge. Instant access to information will be replaced by instant access to knowledge. Understanding the cognitive limitations of humans and the opportunities opened by the development of artificial intelligence and interdisciplinary research necessary to address global challenges is the key to the revitalization of humanities. Artificial intelligence will radically change humanities, from art to political sciences and philosophy, making these disciplines attractive to students and enabling them to go beyond current limitations.Comment: 39 pages, 1 figur

A comprehensive survey on cultural algorithms

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Music Streaming's Impact on Cultural Diversity : Spotify and Recommendation Algorithms as Gatekeepers

The rapid growth of music streaming business has brought significant changes to the music industry, creating new opportunities for artists, labels, and consumers alike. Streaming services, like Spotify, use algorithmic recommendation systems to help users find the content relevant to them from the seemingly endless trove of music. As modern gatekeepers, these services – and the algorithms they use – yield significant power over culture, affecting the rights of both artists and listeners. This thesis examines the music business in the digitalized era, the algorithmic recommendation of music, and its impact on cultural diversity, the right to express and access culture. Additionally, I will examine what kinds of methods the international society, UN at its helm, has proposed to protect cultural rights and diversity.Musiikin suoratoistopalveluiden nopea kasvu on muuttanut musiikkialaa merkittävästi, luoden uusia mahdollisuuksia niin artisteille, levy-yhtiöille kuin kuluttajillekin. Suoratoistoalustat, kuten Spotify, käyttävät suosittelualgoritmeja ja koneoppimista helpottaakseen käyttäjälle relevantin sisällön löytämistä musiikin loputtomasta tulvasta. Moderneina portinvartijoina suoratoistopalveluilla – ja näin myös niiden käyttämillä suosittelualgoritmeilla – on paljon kulttuurista valtaa. Opinnäytetyössäni tutkin, minkälaisia vaikutuksia suoratoistopalveluilla ja suosittelualgoritmeilla, voi olla ihmisoikeuksiin; kulttuuriseen monimuotoisuuteen, ilmaisunvapauteen ja pääsyyn kulttuurin äärelle. Lisäksi tutkin, minkälaisia toimia kansainvälinen yhteisö YK:n johdolla on ehdottanut kulttuuristen oikeuksien turvaamiseksi

LookBook: pioneering Inclusive beauty with artificial intelligence and machine learning algorithms

Technology's imperfections and biases inherited from historical norms are crucial to acknowledge. Rapid perpetuation and amplification of these biases necessitate transparency and proactive measures to mitigate their impact. The online visual culture reinforces Eurocentric beauty ideals through prioritized algorithms and augmented reality filters, distorting reality and perpetuating unrealistic standards of beauty. Narrow beauty standards in technology pose a significant challenge to overcome. Algorithms personalize content, creating "filter bubbles" that reinforce these ideals and limit exposure to diverse representations of beauty. This cycle compels individuals to conform, hindering the embrace of their unique features and alternative definitions of beauty. LookBook counters prevalent narrow beauty standards in technology. It promotes inclusivity and representation through self-expression, community engagement, and diverse visibility. LookBook comprises three core sections: Dash, Books, and Community. In Dash, users curate their experience through personalization algorithms. Books allow users to collect curated content for inspiration and creativity, while Community fosters connections with like-minded individuals. Through LookBook, users create a reality aligned with their unique vision. They control consumed content, nurturing individualism through preferences and creativity. This personalization empowers individuals to break free from narrow beauty standards and embrace their distinctiveness. LookBook stands out with its algorithmic training and data representation. It offers transparency on how personalization algorithms operate and ensures a balanced and diverse representation of physicalities and ethnicities. By addressing biases and embracing a wide range of identities, LookBook sparks a conversation for a technology landscape that amplifies all voices, fostering an environment celebrating diversity and prioritizing inclusivity