Proceedings of the 14th ACM Web Science Conference 2022最新文献

Characterizing the Social Ties between Black and Tech Communities on Twitter 在推特上刻画黑人和科技社区之间的社会关系

Proceedings of the 14th ACM Web Science Conference 2022 Pub Date : 2022-06-26 DOI: 10.1145/3501247.3531544

Marisa Vasconcelos, Priscila Rocha, J. Nogima, R. Paula

{"title":"Characterizing the Social Ties between Black and Tech Communities on Twitter","authors":"Marisa Vasconcelos, Priscila Rocha, J. Nogima, R. Paula","doi":"10.1145/3501247.3531544","DOIUrl":"https://doi.org/10.1145/3501247.3531544","url":null,"abstract":"The slow increasing rate of representation of women and other minorities, particularly in Information Technology (IT) companies, suggests that the current recruiting strategies for attracting underrepresented minorities (URMs) may not be effective. While much can be done to improve hiring strategies, little attention has been paid to how job seekers’ perceptions (positive or otherwise) of a company may affect its attractiveness. For instance, newer generations of professionals are more likely to avoid companies that are not committed to diversity causes. Studies have in fact shown that job seekers increasingly rely on social media to inform themselves about targeted companies. In this paper, we investigate the “social-mediascape” of Black Tech communities and IT companies, namely, the spaces of interactions and communications and their influences on individuals’ perceptions of particular companies. To this end, we look into the Twitter Black and Tech communities in Brazil and in the United States. We rely on “Twitter lists” that are curated by the users of the platform and effective in capturing topical homophily. A research challenge in itself, we provide the first large-scale compositions of Black Tech communities and their connection to IT companies based on followership data on Twitter. After analyzing these compositions, we can then create perceptual maps between communities and IT companies. Our results suggest that there is a stronger correlation between Black activism and technology in the US context. For the Brazilian context, we found a stronger correlation between the Black Tech and general Software Developer users communities suggesting that both racial activism and technology are important topics to attract the Brazilian Black Tech community’s interests.","PeriodicalId":136381,"journal":{"name":"Proceedings of the 14th ACM Web Science Conference 2022","volume":"166 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114057160","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

Documenting Web Data for Social Research (#DocuWeb22): A participatory workshop for developing structured and reusable practices 为社会研究记录网络数据(#DocuWeb22):一个开发结构化和可重用实践的参与性研讨会

Proceedings of the 14th ACM Web Science Conference 2022 Pub Date : 2022-06-26 DOI: 10.1145/3501247.3539504

Indira Sen, Leon Fröhling, Katrin Weller

引用次数: 0

LIWC-UD: Classifying Online Slang Terms into LIWC Categories LIWC- ud:将网络俚语分类为LIWC类别

Proceedings of the 14th ACM Web Science Conference 2022 Pub Date : 2022-06-26 DOI: 10.1145/3501247.3531572

Mohamed Bahgat, Steven R. Wilson, Walid Magdy

引用次数: 2

Hostility Detection in Online Hindi-English Code-Mixed Conversations 在线印地语-英语代码混合会话中的敌意检测

Proceedings of the 14th ACM Web Science Conference 2022 Pub Date : 2022-06-26 DOI: 10.1145/3501247.3531579

Aditi Bagora, Kamal Shrestha, Kaushal Kumar Maurya, M. Desarkar

{"title":"Hostility Detection in Online Hindi-English Code-Mixed Conversations","authors":"Aditi Bagora, Kamal Shrestha, Kaushal Kumar Maurya, M. Desarkar","doi":"10.1145/3501247.3531579","DOIUrl":"https://doi.org/10.1145/3501247.3531579","url":null,"abstract":"With the rise in accessibility and popularity of various social media platforms, people have started expressing and communicating their ideas, opinions, and interests online. While these platforms are active sources of entertainment and idea-sharing, they also attract hostile and offensive content equally. Identification of hostile posts is an essential and challenging task. In particular, Hindi-English Code-Mixed online posts of conversational nature (which have a hierarchy of posts, comments, and replies) have escalated the challenges. There are two major challenges: (1) the complex structure of Code-Mixed text and (2) filtering the relevant previous context for a given utterance. To overcome these challenges, in this paper, we propose a novel hierarchical neural network architecture to identify hostile posts/comments/replies in online Hindi-English Code-Mixed conversations. We leverage large multilingual pre-trained (mLPT) models like mBERT, XLMR, and MuRIL. The mLPT models provide a rich representation of code-mix text and hierarchical modeling leads to a natural abstraction and selection of the relevant context. The propose model consistently outperformed all the baselines and emerged as a state-of-the-art performing model. We conducted multiple analyses and ablation studies to prove the robustness of the proposed model.","PeriodicalId":136381,"journal":{"name":"Proceedings of the 14th ACM Web Science Conference 2022","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132518388","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

Multi-task Models for Multi-faceted Classification of Pandemic Information on Social Media 社交媒体上流行病信息多面分类的多任务模型

Proceedings of the 14th ACM Web Science Conference 2022 Pub Date : 2022-06-26 DOI: 10.1145/3501247.3531552

Xinchen Yu, Zhuoli Xie, A. Mashhadi, Lingzi Hong

{"title":"Multi-task Models for Multi-faceted Classification of Pandemic Information on Social Media","authors":"Xinchen Yu, Zhuoli Xie, A. Mashhadi, Lingzi Hong","doi":"10.1145/3501247.3531552","DOIUrl":"https://doi.org/10.1145/3501247.3531552","url":null,"abstract":"Social media data such as tweets have been seen as a convenient source of information to enhance situational awareness, and to assist local governments in decision making and response actions in crisis. However, extracting the relevant information for different types of situational awareness has been challenging. Existing studies have investigated classifications of crisis information on social media, but not much focus has been put on the classification of pandemic related information. Pandemics are public health related crisis that present unique characteristics. We propose to classify pandemic tweets from three perspectives, i.e., informativeness, geographic view, and information source, after a comprehensive analysis of the factors determining the relevance of information to situational awareness. The joint use of three-faceted classifications will enable the identification of relevant data for multiple purposes of situational awareness. We manually annotate a dataset with COVID-19 tweets and explore multi-task learning models for the classification of three tasks simultaneously. The proposed multi-task neural network models show improved performance compared with single learning models. We also find that pretraining multi-task models with relevant crisis datasets can further boost the performance. Specifically, multi-task models can significantly increase the recall of ‘informative’ and ‘local’ tweets, which are important for local response actions and policy decision making.","PeriodicalId":136381,"journal":{"name":"Proceedings of the 14th ACM Web Science Conference 2022","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124861934","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: 1

A Tale of Two Sides: Study of Protesters and Counter-protesters on #CitizenshipAmendmentAct Campaign on Twitter 两面的故事:推特上#公民修正法案#运动的抗议者和反抗议者研究

Proceedings of the 14th ACM Web Science Conference 2022 Pub Date : 2022-06-26 DOI: 10.1145/3501247.3531584

Kumari Neha, Vibhu Agrawal, Vishwesh Kumar, Tushar Mohan, Abhishek Chopra, Arun Balaji Buduru, Rajesh Sharma, P. Kumaraguru

{"title":"A Tale of Two Sides: Study of Protesters and Counter-protesters on #CitizenshipAmendmentAct Campaign on Twitter","authors":"Kumari Neha, Vibhu Agrawal, Vishwesh Kumar, Tushar Mohan, Abhishek Chopra, Arun Balaji Buduru, Rajesh Sharma, P. Kumaraguru","doi":"10.1145/3501247.3531584","DOIUrl":"https://doi.org/10.1145/3501247.3531584","url":null,"abstract":"Online social media platforms have evolved into a significant place for debate around socio-political phenomena such as government policies and bills. Studying online debates on such topics can help infer people’s perception and acceptance of the happenings. At the same time, various inauthentic users that often pollute the democratic discussion of the subject need to be weeded out from the debate. The characterization of a campaign keeping in mind various forms of involved actors thus becomes very important. On December 12, 2019, Citizenship Amendment Act (CAA) was enacted by the Indian Government, triggering a debate on whether the act was unfair. In this work, we investigate the user’s perception of the #CitizenshipAmendmentAct on Twitter, as the campaign unrolled with divergent discourse in the country. Keeping the campaign participants as the prime focus, we study 9,947,814 tweets produced by 275,111 users during the starting 3 months of protest. Our study includes the analysis of user engagement, content, and network properties with online accounts divided into authentic (genuine users) and inauthentic (bots, suspended, and deleted) users. Our findings show different themes in shared tweets among protesters and counter-protesters. We find presence of inauthentic users on both side of discourse, with counter-protesters having more inauthentic users than protesters. The follow network of the users suggests homophily among users on the same side of discourse and connection between various inauthentic and authentic users. This work contributes to filling the gap of understanding the role of users (from both sides) in a less studied geo-location, India.","PeriodicalId":136381,"journal":{"name":"Proceedings of the 14th ACM Web Science Conference 2022","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126715284","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

On pushing DeepFake Tweet Detection capabilities to the limits 关于将DeepFake推特检测能力推向极限

Proceedings of the 14th ACM Web Science Conference 2022 Pub Date : 2022-06-26 DOI: 10.1145/3501247.3531560

Margherita Gambini, T. Fagni, F. Falchi, M. Tesconi

{"title":"On pushing DeepFake Tweet Detection capabilities to the limits","authors":"Margherita Gambini, T. Fagni, F. Falchi, M. Tesconi","doi":"10.1145/3501247.3531560","DOIUrl":"https://doi.org/10.1145/3501247.3531560","url":null,"abstract":"The recent advances in natural language generation provide an additional tool to manipulate public opinion on social media. Even though there has not been any report of malicious exploit of the newest generative techniques so far, disturbing human-like scholarly examples of GPT-2 and GPT-3 can be found on social media. Therefore, our paper investigates how the state-of-the-art deepfake social media text detectors perform at recognizing GPT-2 tweets as machine-written, also trying to improve the state-of-the-art by hyper-parameter tuning and ensembling the most promising detectors; finally, our work concentrates on studying the detectors’ capabilities to generalize over tweets generated by the more sophisticated and complex evolution of GPT-2, that is GPT-3. Results demonstrate that hyper-parameter optimization and ensembling advance the state-of-the-art, especially on the detection of GPT-2 tweets. However, all tested detectors dramatically decreased their accuracy on GPT-3 tweets. Despite this, we found out that even though GPT-3 tweets are much closer to human-written tweets than the ones produced by GPT-2, they still have latent features in common share with other generative techniques like GPT-2, RNN and other older methods. All things considered, the research community should quickly devise methods to detect GPT-3 social media texts, as well as older generative methods.","PeriodicalId":136381,"journal":{"name":"Proceedings of the 14th ACM Web Science Conference 2022","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132353340","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: 19

Shift of User Attitudes about Anti-Asian Hate on Reddit Before and During COVID-19 在COVID-19之前和期间，用户对Reddit上反亚洲仇恨的态度转变

Proceedings of the 14th ACM Web Science Conference 2022 Pub Date : 2022-06-26 DOI: 10.1145/3501247.3531569

L. Manikonda, Mee Young Um, Rui Fan

{"title":"Shift of User Attitudes about Anti-Asian Hate on Reddit Before and During COVID-19","authors":"L. Manikonda, Mee Young Um, Rui Fan","doi":"10.1145/3501247.3531569","DOIUrl":"https://doi.org/10.1145/3501247.3531569","url":null,"abstract":"Content Warning: This paper shows examples of explicit and offensive language that might be triggering. The main goal of this paper is to investigate the temporal shifts of attitudes about racism towards Asians using online social media posts. An increase in race-related crimes towards Asian communities during COVID-19 is the prime motivation of the work presented in this paper. Towards this goal, social media data from Reddit that were shared between January 2018 and December 2021 are utilized to examine the user attitudes towards anti-Asian hate along with the temporal shifts in those attitudes. Using natural language processing techniques, this study conducts a quantitative investigation on how linguistic emotions are expressed in user posts as well as the engagement received by such posts. Our data suggest that anti-Asian hate crimes or incidents have been discussed long before COVID-19, but it is during the pandemic when we noticed a sharp increase in the number of posts about this topic. Psycholinguistic emotions highlight the surge of posts from users sharing about their personal experiences during the pandemic. Topics extracted show the shift of discussions from relating anti-Asian hate crimes to different types of phobias to issues that are more related to personal encounters or private lives/opinions of users during COVID-19. Our work used “score” as a metric to measure online support, which shows an increase of support to users and an increased agreement with the posts the users are sharing on Reddit during the pandemic.","PeriodicalId":136381,"journal":{"name":"Proceedings of the 14th ACM Web Science Conference 2022","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114682429","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: 1

The Disinformation Dozen: An Exploratory Analysis of Covid-19 Disinformation Proliferation on Twitter 虚假信息十二个:对推特上新冠肺炎虚假信息扩散的探索性分析

Proceedings of the 14th ACM Web Science Conference 2022 Pub Date : 2022-06-26 DOI: 10.1145/3501247.3531573

Gianluca Nogara, Padinjaredath Suresh Vishnuprasad, Felipe Cardoso, Omran Ayoub, Silvia Giordano, Luca Luceri

{"title":"The Disinformation Dozen: An Exploratory Analysis of Covid-19 Disinformation Proliferation on Twitter","authors":"Gianluca Nogara, Padinjaredath Suresh Vishnuprasad, Felipe Cardoso, Omran Ayoub, Silvia Giordano, Luca Luceri","doi":"10.1145/3501247.3531573","DOIUrl":"https://doi.org/10.1145/3501247.3531573","url":null,"abstract":"Shortly after the outbreak of the novel coronavirus disease (Covid-19), the United Nations declared an infodemic due to an unprecedented amount of false information spreading about Covid-19. A study made by the center for countering digital hate found out that twelve individuals, referred to as Disinformation Dozen (Disinfo12), were responsible for 65% of Covid-19 misinformation circulating on social media. Given the Disinfo12’s detrimental impact in spreading misinformation, in this work, we perform an exploratory analysis on Disinfo12’s activity on Twitter aiming at identifying their sharing strategies, favorite sources of information, and potential secondary actors contributing to the proliferation of questionable narratives. In our study, we uncovered the distinctive facets that allowed Disinfo12 to act as primary sources of information, and we recognized that YouTube represent one of the favorite information sources to spread questionable narratives and conspiracy theories. Finally, we recognized that right-leaning accounts are embedded in Disinfo12’s community and represent the main spreaders of content generated by the Disinformation Dozen.","PeriodicalId":136381,"journal":{"name":"Proceedings of the 14th ACM Web Science Conference 2022","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123203166","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: 24

Blockchain for Social Good: Combating Misinformation on the Web with AI and Blockchain 区块链社会公益:用人工智能和区块链打击网络上的错误信息

Proceedings of the 14th ACM Web Science Conference 2022 Pub Date : 2022-06-26 DOI: 10.1145/3501247.3539016

O. Seneviratne

{"title":"Blockchain for Social Good: Combating Misinformation on the Web with AI and Blockchain","authors":"O. Seneviratne","doi":"10.1145/3501247.3539016","DOIUrl":"https://doi.org/10.1145/3501247.3539016","url":null,"abstract":"The spread of deceptive or misleading information, commonly referred to as misinformation, poses a social, economic, and political threat. Such deceptive information spreads quickly and inexpensively. For example, with the hype around blockchain technologies, misinformation on “get rich quick” scams on the Web is rampant, as evidenced by sophisticated Twitter hacks of celebrities and many social media posts that bait unsuspecting users to visit phishing websites. Unfortunately, AI technologies have contributed to the growing pains of misinformation on the Web, with the advances in technologies such as generative adversarial deep learning techniques that can generate “deep fakes” for nefarious purposes. At the same time, researchers are working on a different set of AI technologies to combat misinformation, akin to “fighting fire with fire.” As there is no clear way to win the online “cat-and-mouse” game against fake news generators and spreaders of misinformation, we believe social media platforms could be fortified with blockchain and AI technologies to mitigate the extent of misinformation propagation in various communities worldwide. Tamper-proof blockchain techniques can provide irrefutable evidence of what content is authentic, guaranteeing how the information has evolved with provenance trails. Various AI models that could be used for detecting fake news can be served on a blockchain for the effective and transparent utility of the model. Such a synergistic combination of AI and blockchain is a burgeoning area of research. This paper outlines a proposal for combining blockchain and AI techniques for handling misinformation on the Web and highlights some of the early ongoing work in this space.","PeriodicalId":136381,"journal":{"name":"Proceedings of the 14th ACM Web Science Conference 2022","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128997644","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