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Small-area population forecasting in a segregated city using density-functional fluctuation theory. 利用密度函数波动理论预测隔离城市的小区域人口。
IF 2.3
Journal of Computational Social Science Pub Date : 2024-01-01 Epub Date: 2024-08-28 DOI: 10.1007/s42001-024-00305-3
Yuchao Chen, Yunus A Kinkhabwala, Boris Barron, Matthew Hall, Tomás A Arias, Itai Cohen
{"title":"Small-area population forecasting in a segregated city using density-functional fluctuation theory.","authors":"Yuchao Chen, Yunus A Kinkhabwala, Boris Barron, Matthew Hall, Tomás A Arias, Itai Cohen","doi":"10.1007/s42001-024-00305-3","DOIUrl":"10.1007/s42001-024-00305-3","url":null,"abstract":"<p><p>Policy decisions concerning housing, transportation, and resource allocation would all benefit from accurate small-area population forecasts. However, despite the success of regional-scale migration models, developing neighborhood-scale forecasts remains a challenge due to the complex nature of residential choice. Here, we introduce an innovative approach to this challenge by extending density-functional fluctuation theory (DFFT), a proven approach for modeling group spatial behavior in biological systems, to predict small-area population shifts over time. The DFFT method uses observed fluctuations in small-area populations to disentangle and extract effective social and spatial drivers of segregation, and then uses this information to forecast intra-regional migration. To demonstrate the efficacy of our approach in a controlled setting, we consider a simulated city constructed from a Schelling-type model. Our findings indicate that even without direct access to the underlying agent preferences, DFFT accurately predicts how broader demographic changes at the city scale percolate to small-area populations. In particular, our results demonstrate the ability of DFFT to incorporate the impacts of segregation into small-area population forecasting using interactions inferred solely from steady-state population count data.</p>","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"7 3","pages":"2255-2275"},"PeriodicalIF":2.3,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11541354/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142629126","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: 0
Impact of income inequality on health and education in Africa: the long-run role of public spending with short-run dynamics 收入不平等对非洲卫生和教育的影响：公共支出的长期作用与短期动态变化
IF 3.2
Journal of Computational Social Science Pub Date : 2023-12-16 DOI: 10.1007/s42001-023-00237-4
Tonmoy Chatterjee, Ghirmai Tesfamariam Teame, Sharmi Sen
{"title":"Impact of income inequality on health and education in Africa: the long-run role of public spending with short-run dynamics","authors":"Tonmoy Chatterjee, Ghirmai Tesfamariam Teame, Sharmi Sen","doi":"10.1007/s42001-023-00237-4","DOIUrl":"https://doi.org/10.1007/s42001-023-00237-4","url":null,"abstract":"","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"55 12","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138967729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An empirical study of sentiment analysis utilizing machine learning and deep learning algorithms 利用机器学习和深度学习算法进行情感分析的实证研究
IF 3.2
Journal of Computational Social Science Pub Date : 2023-12-09 DOI: 10.1007/s42001-023-00236-5
Betul Erkantarci, Gokhan Bakal
{"title":"An empirical study of sentiment analysis utilizing machine learning and deep learning algorithms","authors":"Betul Erkantarci, Gokhan Bakal","doi":"10.1007/s42001-023-00236-5","DOIUrl":"https://doi.org/10.1007/s42001-023-00236-5","url":null,"abstract":"","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"9 7","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138585535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The risk co-de model: detecting psychosocial processes of risk perception in natural language through machine learning 风险共感模型：通过机器学习检测自然语言中风险认知的社会心理过程
IF 3.2
Journal of Computational Social Science Pub Date : 2023-11-30 DOI: 10.1007/s42001-023-00235-6
Valentina Rizzoli
{"title":"The risk co-de model: detecting psychosocial processes of risk perception in natural language through machine learning","authors":"Valentina Rizzoli","doi":"10.1007/s42001-023-00235-6","DOIUrl":"https://doi.org/10.1007/s42001-023-00235-6","url":null,"abstract":"","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"1701 ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139204082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Exploring statistical approaches for predicting student dropout in education: a systematic review and meta-analysis 探索预测学生辍学的统计方法：系统回顾与荟萃分析
IF 3.2
Journal of Computational Social Science Pub Date : 2023-11-29 DOI: 10.1007/s42001-023-00231-w
Raghul Gandhi Venkatesan, Dhivya Karmegam, Bagavandas Mappillairaju
{"title":"Exploring statistical approaches for predicting student dropout in education: a systematic review and meta-analysis","authors":"Raghul Gandhi Venkatesan, Dhivya Karmegam, Bagavandas Mappillairaju","doi":"10.1007/s42001-023-00231-w","DOIUrl":"https://doi.org/10.1007/s42001-023-00231-w","url":null,"abstract":"","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"5 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139209369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Automated measures of sentiment via transformer- and lexicon-based sentiment analysis (TLSA) 通过基于转换器和词典的情感分析（TLSA）自动测量情感
IF 3.2
Journal of Computational Social Science Pub Date : 2023-11-21 DOI: 10.1007/s42001-023-00233-8
Xinyan Zhao, Chau-Wai Wong
{"title":"Automated measures of sentiment via transformer- and lexicon-based sentiment analysis (TLSA)","authors":"Xinyan Zhao, Chau-Wai Wong","doi":"10.1007/s42001-023-00233-8","DOIUrl":"https://doi.org/10.1007/s42001-023-00233-8","url":null,"abstract":"","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"164 5","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139251770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A fuzzy set extension of Schelling’s spatial segregation model 谢林空间隔离模型的模糊集扩展
IF 3.2
Journal of Computational Social Science Pub Date : 2023-11-20 DOI: 10.1007/s42001-023-00234-7
Atsushi Ishida
{"title":"A fuzzy set extension of Schelling’s spatial segregation model","authors":"Atsushi Ishida","doi":"10.1007/s42001-023-00234-7","DOIUrl":"https://doi.org/10.1007/s42001-023-00234-7","url":null,"abstract":"","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"11 2","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139259627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Integrating the gender dimension to disclose the degree of businesses’ articulation of innovation 整合性别维度，披露企业的创新衔接程度
IF 3.2
Journal of Computational Social Science Pub Date : 2023-11-19 DOI: 10.1007/s42001-023-00230-x
Giacomo di Tollo, Joseph Andria, S. Tanev, Sara Ghilardi
{"title":"Integrating the gender dimension to disclose the degree of businesses’ articulation of innovation","authors":"Giacomo di Tollo, Joseph Andria, S. Tanev, Sara Ghilardi","doi":"10.1007/s42001-023-00230-x","DOIUrl":"https://doi.org/10.1007/s42001-023-00230-x","url":null,"abstract":"","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"3 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139260094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A study of the effect of influential spreaders on the different sectors of Indian market and a few foreign markets: a complex networks perspective 有影响力的传播者对印度市场和少数外国市场不同部门的影响研究:复杂网络视角
Journal of Computational Social Science Pub Date : 2023-11-14 DOI: 10.1007/s42001-023-00229-4
Anwesha Sengupta, Shashankaditya Upadhyay, Indranil Mukherjee, Prasanta K. Panigrahi
{"title":"A study of the effect of influential spreaders on the different sectors of Indian market and a few foreign markets: a complex networks perspective","authors":"Anwesha Sengupta, Shashankaditya Upadhyay, Indranil Mukherjee, Prasanta K. Panigrahi","doi":"10.1007/s42001-023-00229-4","DOIUrl":"https://doi.org/10.1007/s42001-023-00229-4","url":null,"abstract":"","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"1 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134991829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Predictive insights: leveraging Twitter sentiments and machine learning for environmental, social and governance controversy prediction 预测洞察:利用Twitter情绪和机器学习进行环境、社会和治理争议预测
Journal of Computational Social Science Pub Date : 2023-10-28 DOI: 10.1007/s42001-023-00228-5
Yasemin Lheureux
{"title":"Predictive insights: leveraging Twitter sentiments and machine learning for environmental, social and governance controversy prediction","authors":"Yasemin Lheureux","doi":"10.1007/s42001-023-00228-5","DOIUrl":"https://doi.org/10.1007/s42001-023-00228-5","url":null,"abstract":"","PeriodicalId":29946,"journal":{"name":"Journal of Computational Social Science","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136160463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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