Quantitative Analysis of Cultural Dynamics Seen from an Event-based
Social Network
- URL: http://arxiv.org/abs/2306.06176v1
- Date: Fri, 9 Jun 2023 18:02:45 GMT
- Title: Quantitative Analysis of Cultural Dynamics Seen from an Event-based
Social Network
- Authors: Bayu Adhi Tama, Jaehong Kim, Jaehyuk Park, Lev Manovich, Meeyoung Cha
- Abstract summary: We analyze the temporal and categorical event dynamics driven by cultural diversity using over 2 million event logs collected over 17 years in 90 countries.
Our results show that the national economic status explains 44.6 percent of the variance in total event count, while cultural characteristics such as individualism and long-term orientation explain 32.8 percent of the variance in topic categories.
- Score: 11.936224646590802
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Culture is a collection of connected and potentially interactive patterns
that characterize a social group or a passed-on idea that people acquire as
members of society. While offline activities can provide a better picture of
the geographical association of cultural traits than online activities,
gathering such data on a large scale has been challenging. Here, we use
multi-decade longitudinal records of cultural events from Meetup.com, the
largest event-based social networking service, to examine the landscape of
offline cultural events. We analyze the temporal and categorical event dynamics
driven by cultural diversity using over 2 million event logs collected over 17
years in 90 countries. Our results show that the national economic status
explains 44.6 percent of the variance in total event count, while cultural
characteristics such as individualism and long-term orientation explain 32.8
percent of the variance in topic categories. Furthermore, our analysis using
hierarchical clustering reveals cultural proximity between the topics of
socio-cultural activities (e.g., politics, leisure, health, technology). We
expect that this work provides a landscape of social and cultural activities
across the world, which allows us to better understand their dynamical patterns
as well as their associations with cultural characteristics.
Related papers
- Schema-Guided Culture-Aware Complex Event Simulation with Multi-Agent Role-Play [69.57968387772428]
Complex news events, such as natural disasters and socio-political conflicts, require swift responses from the government and society.
We develop a controllable complex news event simulator guided by both the event schema representing domain knowledge.
We introduce a geo-diverse commonsense and cultural norm-aware knowledge enhancement component.
arXiv Detail & Related papers (2024-10-24T17:21:43Z) - Extrinsic Evaluation of Cultural Competence in Large Language Models [53.626808086522985]
We focus on extrinsic evaluation of cultural competence in two text generation tasks.
We evaluate model outputs when an explicit cue of culture, specifically nationality, is perturbed in the prompts.
We find weak correlations between text similarity of outputs for different countries and the cultural values of these countries.
arXiv Detail & Related papers (2024-06-17T14:03:27Z) - CulturePark: Boosting Cross-cultural Understanding in Large Language Models [63.452948673344395]
This paper introduces CulturePark, an LLM-powered multi-agent communication framework for cultural data collection.
It generates high-quality cross-cultural dialogues encapsulating human beliefs, norms, and customs.
We evaluate these models across three downstream tasks: content moderation, cultural alignment, and cultural education.
arXiv Detail & Related papers (2024-05-24T01:49:02Z) - What You Use is What You Get: Unforced Errors in Studying Cultural Aspects in Agile Software Development [2.9418191027447906]
Investigating the influence of cultural characteristics is challenging due to the multi-faceted concept of culture.
Cultural and social aspects are of high importance for their successful use in practice.
arXiv Detail & Related papers (2024-04-25T20:08:37Z) - Massively Multi-Cultural Knowledge Acquisition & LM Benchmarking [48.21982147529661]
This paper introduces a novel approach for massively multicultural knowledge acquisition.
Our method strategically navigates from densely informative Wikipedia documents on cultural topics to an extensive network of linked pages.
Our work marks an important step towards deeper understanding and bridging the gaps of cultural disparities in AI.
arXiv Detail & Related papers (2024-02-14T18:16:54Z) - Cultural Differences in Friendship Network Behaviors: A Snapchat Case
Study [0.0]
We analyzed the friendship networks and dyadic relations between content producers and consumers across 73 countries.
We studied three theoretical frameworks of culture - individualism, relational mobility, and tightness.
Our work has implications for content recommendations and can improve content engagement.
arXiv Detail & Related papers (2023-01-29T22:44:54Z) - Classification of Cross-cultural News Events [0.685316573653194]
We group countries based on the culture that they follow and then filter the news events based on their content category.
We present combinations of events across different categories and check the performances of different classification methods.
arXiv Detail & Related papers (2023-01-13T13:41:18Z) - Measuring Commonality in Recommendation of Cultural Content: Recommender
Systems to Enhance Cultural Citizenship [67.5613995938273]
We introduce commonality as a new measure that reflects the degree to which recommendations familiarize a given user population with specified categories of cultural content.
Our results demonstrate that commonality captures a property of system behavior complementary to existing metrics and suggest the need for alternative, non-personalized interventions in recommender systems oriented to strengthening cultural citizenship across populations of users.
arXiv Detail & Related papers (2022-08-02T19:14:49Z) - From Culture to Clothing: Discovering the World Events Behind A Century
of Fashion Images [100.20851232528925]
We propose a data-driven approach to identify specific cultural factors affecting the clothes people wear.
Our work is a first step towards a computational, scalable, and easily refreshable approach to link culture to clothing.
arXiv Detail & Related papers (2021-02-02T18:58:21Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.