Social Science Computer Review最新文献_第4页

Understanding Narratives of Uncertainty in Fertility Intentions of Dutch Women: A Neural Topic Modeling Approach 理解荷兰妇女生育意愿中的不确定性叙述：神经主题建模方法

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-08-24 DOI: 10.1177/08944393241269406

Xiao Xu, Anne Gauthier, Gert Stulp, Antal van den Bosch

{"title":"Understanding Narratives of Uncertainty in Fertility Intentions of Dutch Women: A Neural Topic Modeling Approach","authors":"Xiao Xu, Anne Gauthier, Gert Stulp, Antal van den Bosch","doi":"10.1177/08944393241269406","DOIUrl":"https://doi.org/10.1177/08944393241269406","url":null,"abstract":"Uncertainty in fertility intentions is a major obstacle to understanding contemporary trends in fertility decision-making and its outcomes. Quantifying this uncertainty by structural factors such as income, ethnicity, and housing conditions is recognized as insufficient. A recently proposed framework on subjective narratives has opened up a new way to gauge factors behind fertility decision-making and uncertainty. Through surveys, such narratives can be elicited with open-ended questions (OEQs). However, analyzing answers to OEQs typically involves extensive human coding, imposing constraints on sample size. Natural Language Processing (NLP) techniques assist researchers in grasping aspects of the underlying reasoning behind responses with much less human effort. In this study, using automatic neural topic modeling methods, we identify and interpret topics and themes underlying the narratives on fertility intention uncertainty of women in the Netherlands. We used Contextualized Topic Models (CTMs), a neural topic model using pre-trained representations of Dutch language, to conduct our analyses. Our results show that nine topics dominate the narratives about fertility planning, with age and health-related issues as the most prominent ones. In addition, we found that uncertainty in fertility intentions is not homogeneous, as women who feel uncertain due to real-life constraints and those who have no fertility plans at all put their stress on vastly different narratives.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"25 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142050627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Video Game Feedback Learning and Aggressive or Prosocial Effects 电子游戏反馈学习与攻击性或亲社会效应

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-08-23 DOI: 10.1177/08944393241277556

Boyu Qiu, Wei Zhang

引用次数: 0

Agents of Discord: Modeling the Impact of Political Bots on Opinion Polarization in Social Networks 不和谐代理：模拟政治机器人对社交网络舆论两极分化的影响

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-08-16 DOI: 10.1177/08944393241270382

Hsiu-Chi Lu, Hsuan-wei Lee

{"title":"Agents of Discord: Modeling the Impact of Political Bots on Opinion Polarization in Social Networks","authors":"Hsiu-Chi Lu, Hsuan-wei Lee","doi":"10.1177/08944393241270382","DOIUrl":"https://doi.org/10.1177/08944393241270382","url":null,"abstract":"The pervasive presence and influence of political bots have become the subject of extensive research in recent years. Studies have revealed that a significant percentage of active accounts are bots, contributing to the polarization of public sentiment online. This study employs an agent-based model in conducting computer simulations of complex social networks, to elucidate how bots, representing diverse ideological perspectives, exacerbate societal divisions. To investigate the dynamics of opinion diffusion and shed light on the phenomenon of polarization caused by the activities of political bots, we introduced bots into a bounded-confidence opinion dynamic model for different social networks, whereby the effects of bots on other agents were studied to provide a comprehensive understanding of their influence on opinion dynamics. The simulations showed that the symmetrical deployment of bots on both sides of the opinion spectrum intensifies polarization. These effects were observed within specific tolerance and homophily ranges, with low and high user tolerances slowing down polarization. Moreover, the average path length of the network and the centrality of the bots had a significant impact on the result. Finally, polarization tends to be lower when humans exhibit reduced confidence in bots. This research not only offers valuable insights into the implications of bot activities on the polarization of public opinion and current state of digital society but also provides suggestions to mitigate bot-driven polarization.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"136 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141994348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using Twitter to Detect Polling Place Issue Reports on U.S. Election Days 使用 Twitter 检测美国大选日投票站问题报告

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-08-10 DOI: 10.1177/08944393241269420

Prathm Juneja, Luciano Floridi

引用次数: 0

Using OpenStreetMap, Census, and Survey Data to Predict Interethnic Group Relations in Belgium: A Machine Learning Approach 利用 OpenStreetMap、人口普查和调查数据预测比利时的族群间关系：机器学习方法

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-08-08 DOI: 10.1177/08944393241269098

Daria Dementeva, Cecil Meeusen, Bart Meuleman

{"title":"Using OpenStreetMap, Census, and Survey Data to Predict Interethnic Group Relations in Belgium: A Machine Learning Approach","authors":"Daria Dementeva, Cecil Meeusen, Bart Meuleman","doi":"10.1177/08944393241269098","DOIUrl":"https://doi.org/10.1177/08944393241269098","url":null,"abstract":"Neighborhoods are important contexts in shaping interethnic group relationships and sites in which these may materialize through everyday routines in shared local spaces. In this paper, we approach neighborhoods as a small-scale set of spaces of encounter, defined as local public or semi-public spaces, where residents of different ethnic backgrounds may meet. Relying on the classical contact and group threat theories, the main assumption is that local spaces of encounter are facets of an intergroup neighborhood context and may shape intergroup relations, defined as perceived ethnic threat and intergroup friendship. Drawing on the georeferenced survey data from the Belgian National Election Study 2020 enriched with spatial features from OpenStreetMap, an innovative big geospatial data source, and census-based neighborhood characteristics, the study employs machine learning algorithms to investigate whether, which, and how neighborhood spaces of encounter can predict perceived ethnic threat and intergroup friendship, while also taking into account traditional local ethnic, socioeconomic, and individual indicators. By using OpenStreetMap to measure spaces of encounter as a novel neighborhood indicator, we develop a fine-grained typology of local spaces that is rooted in urban and intergroup relations research. The results show that for predicting intergroup friendship, the important spaces were educational, functional, public open, and user-selecting spaces, while for predicting threat functional, third, retail, and other spaces stood out prediction-wise. The results also revealed the predictive importance of individual characteristics for intergroup relations, while neighborhood characteristics were not so important, both in absolute and relative terms. We conclude by reflecting on what local spaces might matter and discuss the combination of OpenStreetMap and intergroup relations as a proof of concept and prospects for future research.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"26 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141908960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Airbnb on TikTok: Brand Perception Through User Engagement and Sentiment Trends TikTok 上的 Airbnb：通过用户参与和情绪趋势感知品牌

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-08-08 DOI: 10.1177/08944393241260242

Julia Marti-Ochoa, Eva Martin-Fuentes, Berta Ferrer-Rosell

{"title":"Airbnb on TikTok: Brand Perception Through User Engagement and Sentiment Trends","authors":"Julia Marti-Ochoa, Eva Martin-Fuentes, Berta Ferrer-Rosell","doi":"10.1177/08944393241260242","DOIUrl":"https://doi.org/10.1177/08944393241260242","url":null,"abstract":"This study delves into Airbnb’s brand presence on TikTok by analyzing textual content in posts, and human audio in videos. This approach aims to decipher the brand narrative and gauge user engagement. In the dynamic realm of social media marketing, TikTok has emerged as a key platform in shaping brand perception. This research specifically concentrates on Airbnb’s content, distinguishing between official narratives and user-generated content (UGC). Notably, themes of “Travel” dominate official posts, contrasting with “Real Estate” and “Business” in UGC. The methodology employed involves advanced data collection techniques, including web scraping for textual data and artificial intelligence for transcribing human audio to text. The findings reveal that UGC commands greater engagement and volume compared to Airbnb’s own brand content, underscoring the increasing significance of user involvement in brand storytelling. An analysis of the study results is conducted using linguistic natural processing (LNP) for the sentiment base, and the vector space model for emotion analysis. Sentiment analysis reveals a predominance of the emotion “happiness” and a significant presence of “surprise” in the posts, both of which are critical for audience engagement. Moreover, the study indicates a high approval rate for Airbnb-related content, reflecting a positive reception of the brand. Additionally, the research observes that influencers, particularly nano influencers, have higher engagement rates, indicating that their authenticity and relatability appeal especially to Generation Z audiences. This study not only sheds light on the intricate relationship between brand narrative, user engagement, and sentiment on TikTok but also offers valuable insights into effective brand image construction and propagation in the digital era, highlighting the importance of diverse emotions in enhancing audience engagement.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"62 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141908959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gender Gap in All Academic Fields Over Time 所有学术领域的性别差距随时间变化

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-08-08 DOI: 10.1177/08944393241270633

Dariusz Jemielniak, Maciej Wilamowski

引用次数: 0

Sexism and Media Communication. An Application to the Italian Case 性别歧视与媒体传播。意大利案例的应用

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-08-06 DOI: 10.1177/08944393241269415

Elia A. G. Arfini, Luigi Curini, Fabiana G. Giannuzzi

引用次数: 0

Journalists’ Ethical Responsibility: Tackling Hate Speech Against Women Politicians in Social Media Through Natural Language Processing Techniques 记者的道德责任：通过自然语言处理技术应对社交媒体中针对女政治家的仇恨言论

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-08-05 DOI: 10.1177/08944393241269417

Maria Iranzo-Cabrera, Maria Jose Castro-Bleda, Iris Simón-Astudillo, Lluís-F. Hurtado

{"title":"Journalists’ Ethical Responsibility: Tackling Hate Speech Against Women Politicians in Social Media Through Natural Language Processing Techniques","authors":"Maria Iranzo-Cabrera, Maria Jose Castro-Bleda, Iris Simón-Astudillo, Lluís-F. Hurtado","doi":"10.1177/08944393241269417","DOIUrl":"https://doi.org/10.1177/08944393241269417","url":null,"abstract":"Social media has led to a redefinition of the journalist’s role. Specifically on Twitter, these professionals assume an influential position and their discourse is dominated by personal opinions. Taking into consideration that this platform has proven to be a breeding ground for polarization, digital harassment and hate speech, notably against women politicians, this research aims to analyze journalists’ involvement in this complex scenario. The investigation aims to determine whether, immersed in online and gender defamation campaigns, journalists enhance the quality of public debate or, on the contrary, they reinforce the visibility of this hostile content. To this end, we examined a sample of 63,926 tweets published from 23 to 25 November 2022 related to a campaign of political violence against the Spanish Minister of Equality using Natural Language Processing tools and qualitative content analysis. Results show that during those three days, at least half of the tweets contained hate speech and improper language. In this climate of hostility, journalists participating in the debate not only have an ability to attract likes and retweets but also exhibit polarization and use hate speech. Each ideological position—for and against the Minister—is also reflected in their own uncivil strategies. Under the umbrella of free speech and regardless of argumentative discourses, those journalists who lean towards ideological progressivism tend to insult their opponents, and those on the political right use divisive constructions, stereotyping and irony as attack techniques.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"55 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141895575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Forty Thousand Fake Twitter Profiles: A Computational Framework for the Visual Analysis of Social Media Propaganda 四万个虚假 Twitter 简介：社交媒体宣传可视化分析的计算框架

IF 4.1 2区社会学

Social Science Computer Review Pub Date : 2024-08-02 DOI: 10.1177/08944393241269394

Noel George, Azhar Sham, Thanvi Ajith, Marco Bastos

引用次数: 0