Journal of Computational Social Science最新文献_第8页

Social media and suicide in social movements: a case study in Hong Kong 社会运动中的社交媒体与自杀:以香港为例

IF 3.2

Journal of Computational Social Science Pub Date : 2022-03-01 DOI: 10.1007/s42001-022-00159-7

P. Yip, E. Pinkney

引用次数: 3

Fooled by facts: quantifying anchoring bias through a large-scale experiment 被事实愚弄:通过大规模实验量化锚定偏差

IF 3.2

Journal of Computational Social Science Pub Date : 2022-01-13 DOI: 10.1007/s42001-021-00158-0

T. Yasseri, Jannie Reher

引用次数: 6

Extracting multiple layers of social networks through a 7-month survey using a wearable device: a case study from a farming community in Japan. 通过使用可穿戴设备进行为期7个月的调查，提取多层次的社交网络:以日本一个农业社区为例。

IF 3.2

Journal of Computational Social Science Pub Date : 2022-01-01 DOI: 10.1007/s42001-022-00162-y

Masashi Komori, Kosuke Takemura, Yukihisa Minoura, Atsuhiko Uchida, Rino Iida, Aya Seike, Yukiko Uchida

{"title":"Extracting multiple layers of social networks through a 7-month survey using a wearable device: a case study from a farming community in Japan.","authors":"Masashi Komori, Kosuke Takemura, Yukihisa Minoura, Atsuhiko Uchida, Rino Iida, Aya Seike, Yukiko Uchida","doi":"10.1007/s42001-022-00162-y","DOIUrl":"https://doi.org/10.1007/s42001-022-00162-y","url":null,"abstract":"As individuals are susceptible to social influences from those to whom they are connected, structures of social networks have been an important research subject in social sciences. However, quantifying these structures in real life has been comparatively more difficult. One reason is data collection methods-how to assess elusive social contacts (e.g., unintended brief contacts in a coffee room); however, recent studies have overcome this difficulty using wearable devices. Another reason relates to the multi-layered nature of social relations-individuals are often embedded in multiple networks that are overlapping and complicatedly interwoven. A novel method to disentangle such complexity is needed. Here, we propose a new method to detect multiple latent subnetworks behind interpersonal contacts. We collected data of proximities among residents in a Japanese farming community for 7 months using wearable devices which detect other devices nearby via Bluetooth communication. We performed non-negative matrix factorization (NMF) on the proximity log sequences and extracted five latent subnetworks. One of the subnetworks represented social relations regarding farming activities, and another subnetwork captured the patterns of social contacts taking place in a community hall, which played the role of a \"hub\" of diverse residents within the community. We also found that the eigenvector centrality score in the farming-related network was positively associated with self-reported pro-community attitude, while the centrality score regarding the community hall was associated with increased self-reported health.Supplementary information: The online version contains supplementary material available at 10.1007/s42001-022-00162-y.","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"5 1","pages":"1069-1094"},"PeriodicalIF":3.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8908302/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10301739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Measuring spatio-textual affinities in twitter between two urban metropolises. 两个城市大都市推特的空间文本亲和力测量。

IF 3.2

Journal of Computational Social Science Pub Date : 2022-01-01 DOI: 10.1007/s42001-021-00129-5

Minda Hu, Mayank Kejriwal

{"title":"Measuring spatio-textual affinities in twitter between two urban metropolises.","authors":"Minda Hu, Mayank Kejriwal","doi":"10.1007/s42001-021-00129-5","DOIUrl":"https://doi.org/10.1007/s42001-021-00129-5","url":null,"abstract":"With increasing growth of both social media and urbanization, studying urban life through the empirical lens of social media has led to some interesting research opportunities and questions. It is well-recognized that as a 'social animal', most humans are deeply embedded both in their cultural milieu and in broader society that extends well beyond close family, including neighborhoods, communities and workplaces. In this article, we study this embeddedness by leveraging urban dwellers' social media footprint. Specifically, we define and empirically study the issue of spatio-textual affinity by collecting many millions of geotagged tweets collected from two diverse metropolises within the United States: the Boroughs of New York City, and the County of Los Angeles. Spatio-textual affinity is the intuitive hypothesis that tweets coming from similar locations (spatial affinity) will tend to be topically similar (textual affinity). This simple definition of the problem belies the complexity of measuring it, since (re-tweets notwithstanding) two tweets are never truly identical either spatially or textually. Workable definitions of affinity along both dimensions are required, as are appropriate experimental designs, visualizations and measurements. In addition to providing such definitions and a viable framework for conducting spatio-textual affinity experiments on Twitter data, we provide detailed results illustrating how our framework can be used to compare and contrast two important metropolitan areas from multiple perspectives and granularities.","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"5 1","pages":"227-252"},"PeriodicalIF":3.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s42001-021-00129-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9206380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Linguistic, cultural, and narrative capital: computational and human readings of transfer admissions essays. 语言、文化和叙事资本:对转学入学论文的计算和人类解读。

IF 3.2

Journal of Computational Social Science Pub Date : 2022-01-01 Epub Date: 2022-09-30 DOI: 10.1007/s42001-022-00185-5

A J Alvero, Jasmine Pal, Katelyn M Moussavian

{"title":"Linguistic, cultural, and narrative capital: computational and human readings of transfer admissions essays.","authors":"A J Alvero, Jasmine Pal, Katelyn M Moussavian","doi":"10.1007/s42001-022-00185-5","DOIUrl":"https://doi.org/10.1007/s42001-022-00185-5","url":null,"abstract":"Variation in college application materials related to social stratification is a contentious topic in social science and national discourse in the United States. This line of research has also started to use computational methods to consider qualitative materials, such as personal statements and letters of recommendation. Despite the prominence of this topic, fewer studies have considered a fairly common academic pathway: transferring. Approximately 40% of all college students in the US transfer schools at least once. One quirk of the system is that students from community colleges are applying for the same spots for students already enrolled in four year schools and trying to transfer. How might different aspects the transfer application itself correlate with institutional stratification and make students more or less distinguishable? We use a dataset of 20,532 transfer admissions essays submitted to the University of California system to describe how transfer applicants vary linguistically, culturally, and narratively with respect to academic pathways and essay prompts. Using a variety of methods for computational text analysis and qualitative coding, we find that essays written by community college students tend to be distinct from those written by university students. However, the strength and character of these results changed with the writing prompt provided to applicants. These results show how some forms of stratification, such as the type of school students attend, inform educational processes intended to equalize opportunity and how combining computational and human reading might illuminate these patterns.Supplementary information: The online version contains supplementary material available at 10.1007/s42001-022-00185-5.","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"5 2","pages":"1709-1734"},"PeriodicalIF":3.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33517693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Botometer 101: social bot practicum for computational social scientists. Botometer 101：计算社会科学家的社交机器人实践。

IF 2

Journal of Computational Social Science Pub Date : 2022-01-01 Epub Date: 2022-08-20 DOI: 10.1007/s42001-022-00177-5

Kai-Cheng Yang, Emilio Ferrara, Filippo Menczer

引用次数: 0

How he won: Using machine learning to understand Trump’s 2016 victory 他是如何获胜的:利用机器学习来理解特朗普2016年的胜利

IF 3.2

Journal of Computational Social Science Pub Date : 2021-12-28 DOI: 10.1007/s42001-021-00147-3

Zhaochen He, J. Camobreco, K. Perkins

引用次数: 0

Identification of intimate partner violence from free text descriptions in social media 从社交媒体上的自由文本描述识别亲密伴侣暴力

IF 3.2

Journal of Computational Social Science Pub Date : 2021-12-16 DOI: 10.1007/s42001-022-00166-8

Phan Trinh Ha, Rhea D’Silva, Ethan Chen, Mehmet Koyutürk, G. Karakurt

引用次数: 6

OCR with Tesseract, Amazon Textract, and Google Document AI: a benchmarking experiment OCR与Tesseract、Amazon text和Google Document AI:一个基准实验

IF 3.2

Journal of Computational Social Science Pub Date : 2021-11-22 DOI: 10.1007/s42001-021-00149-1

Thomas Hegghammer

引用次数: 9

Determining political interests of issue-motivated groups on social media: joint topic models for issues, sentiment and stance 确定社交媒体上议题驱动群体的政治利益:议题、情绪和立场的联合话题模型

IF 3.2

Journal of Computational Social Science Pub Date : 2021-11-12 DOI: 10.1007/s42001-021-00146-4

Sandeepa Kannangara, W. Wobcke

引用次数: 1