Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science最新文献

Social media data as a lens onto care-seeking behavior among women veterans of the US armed forces 社交媒体数据作为美国武装部队女退伍军人求医行为的一个镜头

Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science Pub Date : 2020-11-01 DOI: 10.18653/v1/2020.nlpcss-1.20

Kacie Kelly, Alex B. Fine, Glen A. Coppersmith

{"title":"Social media data as a lens onto care-seeking behavior among women veterans of the US armed forces","authors":"Kacie Kelly, Alex B. Fine, Glen A. Coppersmith","doi":"10.18653/v1/2020.nlpcss-1.20","DOIUrl":"https://doi.org/10.18653/v1/2020.nlpcss-1.20","url":null,"abstract":"In this article, we examine social media data as a lens onto support-seeking among women veterans of the US armed forces. Social media data hold a great deal of promise as a source of information on needs and support-seeking among individuals who are excluded from or systematically prevented from accessing clinical or other institutions ostensibly designed to support them. We apply natural language processing (NLP) techniques to more than 3 million Tweets collected from 20,000 Twitter users. We find evidence that women veterans are more likely to use social media to seek social and community engagement and to discuss mental health and veterans’ issues significantly more frequently than their male counterparts. By contrast, male veterans tend to use social media to amplify political ideologies or to engage in partisan debate. Our results have implications for how organizations can provide outreach and services to this uniquely vulnerable population, and illustrate the utility of non-traditional observational data sources such as social media to understand the needs of marginalized groups.","PeriodicalId":398724,"journal":{"name":"Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123625103","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: 3

Swimming with the Tide? Positional Claim Detection across Political Text Types 随波逐流?跨政治文本类型的立场主张检测

Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science Pub Date : 2020-11-01 DOI: 10.18653/v1/2020.nlpcss-1.3

Nico Blokker, Erenay Dayanik, Gabriella Lapesa, Sebastian Padó

引用次数: 4

Unsupervised Anomaly Detection in Parole Hearings using Language Models 基于语言模型的假释听证会无监督异常检测

Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science Pub Date : 2020-11-01 DOI: 10.18653/v1/2020.nlpcss-1.8

G. Todd, Catalin Voss, Jenny Hong

引用次数: 1

Identifying Worry in Twitter: Beyond Emotion Analysis 在推特上识别担忧:超越情感分析

Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science Pub Date : 2020-11-01 DOI: 10.18653/v1/2020.nlpcss-1.9

Reyha Verma, C. von der Weth, Jithin Vachery, M. Kankanhalli

{"title":"Identifying Worry in Twitter: Beyond Emotion Analysis","authors":"Reyha Verma, C. von der Weth, Jithin Vachery, M. Kankanhalli","doi":"10.18653/v1/2020.nlpcss-1.9","DOIUrl":"https://doi.org/10.18653/v1/2020.nlpcss-1.9","url":null,"abstract":"Identifying the worries of individuals and societies plays a crucial role in providing social support and enhancing policy decision-making. Due to the popularity of social media platforms such as Twitter, users share worries about personal issues (e.g., health, finances, relationships) and broader issues (e.g., changes in society, environmental concerns, terrorism) freely. In this paper, we explore and evaluate a wide range of machine learning models to predict worry on Twitter. While this task has been closely associated with emotion prediction, we argue and show that identifying worry needs to be addressed as a separate task given the unique challenges associated with it. We conduct a user study to provide evidence that social media posts express two basic kinds of worry – normative and pathological – as stated in psychology literature. In addition, we show that existing emotion detection techniques underperform, especially while capturing normative worry. Finally, we discuss the current limitations of our approach and propose future applications of the worry identification system.","PeriodicalId":398724,"journal":{"name":"Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124105178","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: 4

Foreigner-directed speech is simpler than native-directed: Evidence from social media 来自社交媒体的证据表明，外国人导向语比母语导向语更简单

Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science Pub Date : 2020-11-01 DOI: 10.18653/v1/2020.nlpcss-1.18

Aleksandrs Berdicevskis

{"title":"Foreigner-directed speech is simpler than native-directed: Evidence from social media","authors":"Aleksandrs Berdicevskis","doi":"10.18653/v1/2020.nlpcss-1.18","DOIUrl":"https://doi.org/10.18653/v1/2020.nlpcss-1.18","url":null,"abstract":"I test two hypotheses that play an important role in modern sociolinguistics and language evolution studies: first, that non-native production is simpler than native; second, that production addressed to non-native speakers is simpler than that addressed to natives. The second hypothesis is particularly important for theories about contact-induced simplification, since the accommodation to non-natives may explain how the simplification can spread from adult learners to the whole community. To test the hypotheses, I create a very large corpus of native and non-native written speech in four languages (English, French, Italian, Spanish), extracting data from an internet forum where native languages of the participants are known and the structure of the interactions can be inferred. The corpus data yield inconsistent evidence with respect to the first hypothesis, but largely support the second one, suggesting that foreigner-directed speech is indeed simpler than native-directed. Importantly, when testing the first hypothesis, I contrast production of different speakers, which can introduce confounds and is a likely reason for the inconsistencies. When testing the second hypothesis, the comparison is always within the production of the same speaker (but with different addressees), which makes it more reliable.","PeriodicalId":398724,"journal":{"name":"Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125014775","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: 2

Is Wikipedia succeeding in reducing gender bias? Assessing changes in gender bias in Wikipedia using word embeddings 维基百科在减少性别偏见方面成功了吗?使用词嵌入评估维基百科中性别偏见的变化

Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science Pub Date : 2020-11-01 DOI: 10.18653/v1/2020.nlpcss-1.11

Katja Geertruida Schmahl, T. Viering, S. Makrodimitris, Arman Naseri Jahfari, D. Tax, M. Loog

{"title":"Is Wikipedia succeeding in reducing gender bias? Assessing changes in gender bias in Wikipedia using word embeddings","authors":"Katja Geertruida Schmahl, T. Viering, S. Makrodimitris, Arman Naseri Jahfari, D. Tax, M. Loog","doi":"10.18653/v1/2020.nlpcss-1.11","DOIUrl":"https://doi.org/10.18653/v1/2020.nlpcss-1.11","url":null,"abstract":"Large text corpora used for creating word embeddings (vectors which represent word meanings) often contain stereotypical gender biases. As a result, such unwanted biases will typically also be present in word embeddings derived from such corpora and downstream applications in the field of natural language processing (NLP). To minimize the effect of gender bias in these settings, more insight is needed when it comes to where and how biases manifest themselves in the text corpora employed. This paper contributes by showing how gender bias in word embeddings from Wikipedia has developed over time. Quantifying the gender bias over time shows that art related words have become more female biased. Family and science words have stereotypical biases towards respectively female and male words. These biases seem to have decreased since 2006, but these changes are not more extreme than those seen in random sets of words. Career related words are more strongly associated with male than with female, this difference has only become smaller in recently written articles. These developments provide additional understanding of what can be done to make Wikipedia more gender neutral and how important time of writing can be when considering biases in word embeddings trained from Wikipedia or from other text corpora.","PeriodicalId":398724,"journal":{"name":"Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122453135","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: 13

Predicting independent living outcomes from written reports of social workers 从社会工作者的书面报告中预测独立生活的结果

Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science Pub Date : 2020-11-01 DOI: 10.18653/v1/2020.nlpcss-1.15

Angelika Maier, P. Cimiano

{"title":"Predicting independent living outcomes from written reports of social workers","authors":"Angelika Maier, P. Cimiano","doi":"10.18653/v1/2020.nlpcss-1.15","DOIUrl":"https://doi.org/10.18653/v1/2020.nlpcss-1.15","url":null,"abstract":"In social care environments, the main goal of social workers is to foster independent living by their clients. An important task is thus to monitor progress towards reaching independence in different areas of their patients’ life. To support this task, we present an approach that extracts indications of independence on different life aspects from the day-to-day documentation that social workers create. We describe the process of collecting and annotating a corresponding corpus created from data records of two social work institutions with a focus on disability care. We show that the agreement on the task of annotating the observations of social workers with respect to discrete independent levels yields a high agreement of .74 as measured by Fleiss’ Kappa. We present a classification approach towards automatically classifying an observation into the discrete independence levels and present results for different types of classifiers. Against our original expectation, we show that we reach F-Measures (macro) of 95% averaged across topics, showing that this task can be automatically solved.","PeriodicalId":398724,"journal":{"name":"Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129597976","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

Emoji and Self-Identity in Twitter Bios 推特Bios中的表情符号和自我认同

Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science Pub Date : 2020-11-01 DOI: 10.18653/v1/2020.nlpcss-1.22

Jinhang Li, Giorgos Longinos, Steven R. Wilson, Walid Magdy

{"title":"Emoji and Self-Identity in Twitter Bios","authors":"Jinhang Li, Giorgos Longinos, Steven R. Wilson, Walid Magdy","doi":"10.18653/v1/2020.nlpcss-1.22","DOIUrl":"https://doi.org/10.18653/v1/2020.nlpcss-1.22","url":null,"abstract":"Emoji are widely used to express emotions and concepts on social media, and prior work has shown that users’ choice of emoji reflects the way that they wish to present themselves to the world. Emoji usage is typically studied in the context of posts made by users, and this view has provided important insights into phenomena such as emotional expression and self-representation. In addition to making posts, however, social media platforms like Twitter allow for users to provide a short bio, which is an opportunity to briefly describe their account as a whole. In this work, we focus on the use of emoji in these bio statements. We explore the ways in which users include emoji in these self-descriptions, finding different patterns than those observed around emoji usage in tweets. We examine the relationships between emoji used in bios and the content of users’ tweets, showing that the topics and even the average sentiment of tweets varies for users with different emoji in their bios. Lastly, we confirm that homophily effects exist with respect to the types of emoji that are included in bios of users and their followers.","PeriodicalId":398724,"journal":{"name":"Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129177887","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: 6

Diachronic Embeddings for People in the News 新闻人物的历时嵌入

Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science Pub Date : 2020-11-01 DOI: 10.18653/v1/2020.nlpcss-1.19

Felix Hennig, Steven R. Wilson

引用次数: 1