International Conference on Web and Social Media最新文献_第8页

On the Infrastructure Providers That Support Misinformation Websites 关于支持错误信息网站的基础设施提供商

International Conference on Web and Social Media Pub Date : 2022-05-31 DOI: 10.1609/icwsm.v16i1.19292

Catherine Han, Deepak Kumar, Z. Durumeric

引用次数: 12

Limits of Multilayer Diffusion Network Inference in Social Media Research 多层扩散网络推理在社交媒体研究中的局限性

International Conference on Web and Social Media Pub Date : 2022-05-31 DOI: 10.1609/icwsm.v16i1.19365

Yan Xia, T. H. Chen, Mikko Kivelä

{"title":"Limits of Multilayer Diffusion Network Inference in Social Media Research","authors":"Yan Xia, T. H. Chen, Mikko Kivelä","doi":"10.1609/icwsm.v16i1.19365","DOIUrl":"https://doi.org/10.1609/icwsm.v16i1.19365","url":null,"abstract":"Information on social media spreads through an underlying diffusion network that connects people of common interests and opinions. This diffusion network often comprises multiple layers, each capturing the spreading dynamics of a certain type of information characterized by, for example, topic, language, or attitude. Researchers have previously proposed methods to infer these underlying multilayer diffusion networks from observed spreading patterns, but little is known about how well these methods perform across the range of realistic spreading data. In this paper, we conduct an extensive series of synthetic data experiments to systematically analyze the performance of the multilayer diffusion network inference framework, under varied network structure (e.g. density, number of layers) and information diffusion settings (e.g. cascade size, layer mixing) that are designed to mimic real-world spreading on social media. Our results show extreme performance variation of the inference framework: notably, it achieves much higher accuracy when inferring a denser diffusion network, while it fails to decompose the diffusion network correctly when most cascades in the data reach a limited audience. In demonstrating the conditions under which the inference accuracy is extremely low, our paper highlights the need to carefully evaluate the applicability of the inference before running it on real data. Practically, our results serve as a reference for this evaluation, and our publicly available implementation, which outperforms previous implementations in accuracy, supports further testing under personalized settings.","PeriodicalId":175641,"journal":{"name":"International Conference on Web and Social Media","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128535854","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 Automated Approach to Identifying Corporate Editing 识别公司编辑的自动化方法

International Conference on Web and Social Media Pub Date : 2022-05-31 DOI: 10.1609/icwsm.v16i1.19357

V. Veselovsky, D. Sarkar, T. J. Anderson, R. Soden

引用次数: 4

Cross-Platform Multimodal Misinformation: Taxonomy, Characteristics and Detection for Textual Posts and Videos 跨平台多模态错误信息:文本帖子和视频的分类、特征和检测

International Conference on Web and Social Media Pub Date : 2022-05-31 DOI: 10.1609/icwsm.v16i1.19323

Nicholas Micallef, Marcelo Sandoval-Castañeda, Adir Cohen, M. Ahamad, Srijan, Kumar, Nasir D. Memon

{"title":"Cross-Platform Multimodal Misinformation: Taxonomy, Characteristics and Detection for Textual Posts and Videos","authors":"Nicholas Micallef, Marcelo Sandoval-Castañeda, Adir Cohen, M. Ahamad, Srijan, Kumar, Nasir D. Memon","doi":"10.1609/icwsm.v16i1.19323","DOIUrl":"https://doi.org/10.1609/icwsm.v16i1.19323","url":null,"abstract":"Social media posts that direct users to YouTube videos are one of the most effective techniques for spreading misinformation. However, it has been observed that such posts rarely get deleted or flagged.\u0000Since multi-modal misinformation that leads to compelling videos has more impact than using just textual content, it is important to characterize and detect such textual post and video pairs to prevent users from becoming victims of misinformation. To address this gap, we build a taxonomy of how links to YouTube videos are used on social media platforms. We then use pairs of posts and videos annotated with this taxonomy to test several classification models built using cross-platform features. Our work reveals several characteristics of post-video pairs, in terms of how posts and videos are related to each other, the type of content they share, and their collective outcome.\u0000In addition, we find that traditional approaches to misinformation detection that rely only on text from posts miss a significant number of post-video pairs that contain misinformation.\u0000More importantly, we find that to reduce the spread of misinformation via post-video pairs, classifiers would be more effective if they are designed to use data and features from multiple diverse platforms.","PeriodicalId":175641,"journal":{"name":"International Conference on Web and Social Media","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126107615","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

Improving Wikidata with Student-Generated Concept Maps 用学生生成的概念图改进维基数据

International Conference on Web and Social Media Pub Date : 2022-05-31 DOI: 10.1609/icwsm.v16i1.19285

Hayden Freedman, A. Hoek, Bill Tomlinson

引用次数: 0

Identifying and Characterizing New Expressions of Community Framing during Polarization 极化过程中社区框架新表达的识别与表征

International Conference on Web and Social Media Pub Date : 2022-05-31 DOI: 10.1609/icwsm.v16i1.19339

Hernan Sarmiento, Felipe Bravo-Marquez, Eduardo Graells-Garrido, Bárbara Poblete

{"title":"Identifying and Characterizing New Expressions of Community Framing during Polarization","authors":"Hernan Sarmiento, Felipe Bravo-Marquez, Eduardo Graells-Garrido, Bárbara Poblete","doi":"10.1609/icwsm.v16i1.19339","DOIUrl":"https://doi.org/10.1609/icwsm.v16i1.19339","url":null,"abstract":"Chile experienced a series of important protests between October and December 2019. This social unrest, as it was called, was fueled by social inequity and radically affected the nation's status quo. A large portion of the population demanded a new Constitution and changes to the current government, whereas another part of the population rejected these social demands. This created a highly polarized scenario evidenced through online social media interactions. Analyzing controversial issues that emerge naturally from conversations in online communities can offer a more wide-scale understanding of today's political and societal discussions. Here, we analyze group polarization in social networks by studying the 2019 Chilean social unrest. Specifically, we propose an unsupervised approach for identifying and characterizing community framing (i.e., discovering and understanding polarized concepts). Our approach is based on the sequential application of community detection, topic modeling, and word embedding methods. The novelty of having an unsupervised approach is that it facilitates the performance of scalable and objective framing analyses with minimal human intervention, as it does not require prior domain or network knowledge. Using this methodology, we observe that an apparently similar conversation topic across communities can actually have completely different meanings to each group. We noted, for instance, that while an online community linked the term gente (people) with communism and terrorism, the other associated it with police and military oppression. In this direction, our work can help to contextualize real-world social issues in online platforms, describing how users discuss similar concepts with opposing views.","PeriodicalId":175641,"journal":{"name":"International Conference on Web and Social Media","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131695719","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

Online Social Support via Avatar Communication Buffers Harmful Effects of Offline Bullying Victimization 虚拟形象交流的在线社会支持缓冲了线下欺凌受害的有害影响

International Conference on Web and Social Media Pub Date : 2022-05-31 DOI: 10.1609/icwsm.v16i1.19351

Masanori Takano, K. Yokotani

{"title":"Online Social Support via Avatar Communication Buffers Harmful Effects of Offline Bullying Victimization","authors":"Masanori Takano, K. Yokotani","doi":"10.1609/icwsm.v16i1.19351","DOIUrl":"https://doi.org/10.1609/icwsm.v16i1.19351","url":null,"abstract":"Online social support via avatar communication is a powerful tool for bullying victims because they often lack offline social resources. Additionally, avatar communication allows users rich nonverbal interactions (e.g., emotional expressions) while maintaining online anonymity. This study investigates the role of online social support via avatars for victims and how to facilitate such support. Accordingly, we conducted an online questionnaire survey twice on an avatar communication application, Pigg Party, regarding mental health, offline and online social support, and offline bullying victimization (participants: 3,288 (1st wave) and 758 (2nd wave)). We found that online social support via avatars supplemented insufficient offline social resources, particularly when there was a high risk of offline bullying victimization. Furthermore, we investigated how online social support is improved by ego networks using social network data from Pigg Party. We demonstrated that belonging to large and closely connected communities can enhance online social support. Our findings suggest that avatar communication applications can improve players' mental health through online social support, reinforced by facilitating ego networks.","PeriodicalId":175641,"journal":{"name":"International Conference on Web and Social Media","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115859825","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

Twitter-STMHD: An Extensive User-Level Database of Multiple Mental Health Disorders Twitter-STMHD:多种精神健康障碍的广泛用户级数据库

International Conference on Web and Social Media Pub Date : 2022-05-31 DOI: 10.1609/icwsm.v16i1.19368

Suhavi, A. Singh, Udit Arora, Somyadeep Shrivastava, Aryaveer Singh, R. Shah, P. Kumaraguru

{"title":"Twitter-STMHD: An Extensive User-Level Database of Multiple Mental Health Disorders","authors":"Suhavi, A. Singh, Udit Arora, Somyadeep Shrivastava, Aryaveer Singh, R. Shah, P. Kumaraguru","doi":"10.1609/icwsm.v16i1.19368","DOIUrl":"https://doi.org/10.1609/icwsm.v16i1.19368","url":null,"abstract":"Social Media is equipped with the ability to track and quantify user behavior, establishing it as an appropriate resource for mental health studies. However, previous efforts in the area have been limited by the lack of data and contextually relevant information. There is a need for large-scale, well-labeled mental health datasets with fast reproducible methods to facilitate their heuristic growth. In this paper, we cater to this need by building the Twitter - Self-Reported Temporally-Contextual Mental Health Diagnosis Dataset (Twitter-STMHD), a large scale, user-level dataset grouped into 8 disorder categories and a companion class of control users. The dataset is 60% hand-annotated, which lead to the creation of high-precision self-reported diagnosis report patterns, used for the construction of the rest of the dataset. The dataset, instead of being a corpus of tweets, is a collection of user-profiles of those suffering from mental health disorders to provide a holistic view of the problem statement. By leveraging temporal information, the data for a given profile in the dataset has been collected for disease prevalence periods: onset of disorder, diagnosis and progression, along with a fourth period: COVID-19. This is the only and the largest dataset that captures the tweeting activity of users suffering from mental health disorders during the COVID-19 period.","PeriodicalId":175641,"journal":{"name":"International Conference on Web and Social Media","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128933527","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

Measuring Alignment of Online Grassroots Political Communities with Political Campaigns 衡量在线基层政治社区与政治运动的一致性

International Conference on Web and Social Media Pub Date : 2022-05-31 DOI: 10.1609/icwsm.v16i1.19336

Cameron Raymond, Isaac Waller, Ashton Anderson

{"title":"Measuring Alignment of Online Grassroots Political Communities with Political Campaigns","authors":"Cameron Raymond, Isaac Waller, Ashton Anderson","doi":"10.1609/icwsm.v16i1.19336","DOIUrl":"https://doi.org/10.1609/icwsm.v16i1.19336","url":null,"abstract":"Social media reduces barriers for the formation of large, self-organizing grassroots communities. For political campaigns this poses significant opportunities to address declining party membership, but also reputational risks and potential loss of campaign coherence. While balancing these factors is often done informally, we adopt a behavioural approach by using neural community embeddings to evaluate online communities along cultural, political, and demographic dimensions. We apply this technique to the 2020 U.S. Democratic presidential primaries and the website Reddit, providing novel insights into the important tension between campaigns and third-party actors. Using two benchmark comparison classes, we demonstrate that our embedding dimensions mirror their offline analogues, but more so the views of a candidate's supporters than the candidate's themselves. Finally, we introduce temporal aspects to our community embedding to evaluate the stability of political communities and their interrelations. These analyses serve as an exploration and application of our novel embedding methodology, and give insight into the relationship between online communities and the movements they support.","PeriodicalId":175641,"journal":{"name":"International Conference on Web and Social Media","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129022372","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

PrivacyAlert: A Dataset for Image Privacy Prediction PrivacyAlert:一个图像隐私预测数据集

International Conference on Web and Social Media Pub Date : 2022-05-31 DOI: 10.1609/icwsm.v16i1.19387

Chenye Zhao, J. Mangat, Sujay Koujalgi, A. Squicciarini, Cornelia Caragea

引用次数: 8