{"title":"Demonstration of Weblinks: A Rich Linking Layer Over the Web","authors":"Daniel Roßner, Claus Atzenbeck","doi":"10.1145/3465336.3475123","DOIUrl":"https://doi.org/10.1145/3465336.3475123","url":null,"abstract":"Modern browsers, as we know them from the Web, are used to query and present a variety of different resources. This usually happens by traversing links (i.e., URIs) in hypertext documents. The creation of new links however, is impossible to ordinary users, because they usually are recipients, but not owners of the received resource. In this paper, we demonstrate a browser plugin called \"Weblinks\", which offers its users an additional and rich linking layer over the existing Web. This enhances the notion of links as strings (i.e., URIs) in today's Web context to links as rich objects (n-ary, unidirectional, or bidirectional), which can be created, traversed or shared by anyone using the Weblinks browser plugin.","PeriodicalId":325072,"journal":{"name":"Proceedings of the 32nd ACM Conference on Hypertext and Social Media","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115253293","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}
Pushkal Agarwal, O. Hawkins, Margarita Amaxopoulou, Noel Dempsey, Nishanth R. Sastry, E. Wood
{"title":"Hate Speech in Political Discourse: A Case Study of UK MPs on Twitter","authors":"Pushkal Agarwal, O. Hawkins, Margarita Amaxopoulou, Noel Dempsey, Nishanth R. Sastry, E. Wood","doi":"10.1145/3465336.3475113","DOIUrl":"https://doi.org/10.1145/3465336.3475113","url":null,"abstract":"Online presence is becoming unavoidable for politicians worldwide. In countries such as the UK, Twitter has become the platform of choice, with over 85% (553 of 650) of the Members of Parliament (MPs) having an active online presence. Whereas this has allowed ordinary citizens unprecedented and immediate access to their elected representatives, it has also led to serious concerns about online hate towards MPs. This work attempts to shed light on the problem using a dataset of conversations between MPs and non-MPs over a two month period. Deviating from other approaches in the literature, our data captures entire threads of conversations between Twitter handles of MPs and citizens in order to provide a full context for content that may be flagged as 'hate'. By combining widely-used hate speech detection tools trained on several widely available datasets, we analyse 2.5 million tweets to identify hate speech against MPs and we characterise hate across multiple dimensions of time, topics and MPs' demographics. We find that MPs are subject to intense 'pile on' hate by citizens whereby they get more hate when they are already busy with a high volume of mentions regarding some event or situation. We also show that hate is more dense with regard to certain topics and that MPs who have an ethnic minority background and those holding positions in Government receive more hate than other MPs. We find evidence of citizens expressing negative sentiments while engaging in cross-party conversations, with supporters of one party (e.g. Labour) directing hate against MPs of another party (e.g. Conservative).","PeriodicalId":325072,"journal":{"name":"Proceedings of the 32nd ACM Conference on Hypertext and Social Media","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115951201","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}
A. Singh, Tanmay Sen, S. Saha, Mohammed Hasanuzzaman
{"title":"Federated Multi-task Learning for Complaint Identification from Social Media Data","authors":"A. Singh, Tanmay Sen, S. Saha, Mohammed Hasanuzzaman","doi":"10.1145/3465336.3475119","DOIUrl":"https://doi.org/10.1145/3465336.3475119","url":null,"abstract":"Complaining is a speech act that is often used by consumers to signify a breach of expectation, i.e., an expression of displeasure on a consumer's behalf towards an organization, product, or event. Complaint identification has been previously analyzed based on extensive feature engineering in centralized settings, disregarding the non-identically independently distributed (non-IID), security, and privacy-preserving characteristics of complaints that can hamper data accumulation, distribution, and learning. In this work, we propose a Bidirectional Encoder Representations from Transformers (BERT) based multi-task framework that aims to learn two closely related tasks,viz. complaint identification (primary task) and sentiment classification (auxiliary tasks) concurrently under federated-learning settings. Extensive evaluation on two real-world datasets shows that our proposed framework surpasses the baselines and state-of-the-art framework results by a significant margin.","PeriodicalId":325072,"journal":{"name":"Proceedings of the 32nd ACM Conference on Hypertext and Social Media","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124142118","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}
{"title":"This Item Might Reinforce Your Opinion: Obfuscation and Labeling of Search Results to Mitigate Confirmation Bias","authors":"Alisa Rieger, Tim Draws, M. Theune, N. Tintarev","doi":"10.1145/3465336.3475101","DOIUrl":"https://doi.org/10.1145/3465336.3475101","url":null,"abstract":"During online information search, users tend to select search results that confirm previous beliefs and ignore competing possibilities. This systematic pattern in human behavior is known as confirmation bias. In this paper, we study the effect of obfuscation (i.e., hiding the result unless the user clicks on it) with warning labels and the effect of task on interaction with attitude-confirming search results. We conducted a preregistered, between-subjects crowdsourced user study (N=328) comparing six groups: three levels of obfuscation (targeted, random, none) and two levels of task (joint, two separate) for four debated topics. We found that both types of obfuscation influence user interactions, and in particular that targeted obfuscation helps decrease interaction with attitude-confirming search results. Future work is needed to understand how much of the observed effect is due to the strong influence of obfuscation, versus the warning label or the task design. We discuss design guidelines concerning system goals such as decreasing consumption of attitude-confirming search results, versus nudging users toward a more analytical mode of information processing. We also discuss implications for future work, such as the effects of interventions for confirmation bias mitigation over repeated exposure. We conclude with a strong word of caution: measures such as obfuscations should only be used for the benefit of the user, e.g., when they explicitly consent to mitigating their own biases.","PeriodicalId":325072,"journal":{"name":"Proceedings of the 32nd ACM Conference on Hypertext and Social Media","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133056876","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}
{"title":"RIP Emojis and Words to Contextualize Mourning on Twitter","authors":"Xinyuan Xu, R. Manrique, B. Nunes","doi":"10.1145/3465336.3475100","DOIUrl":"https://doi.org/10.1145/3465336.3475100","url":null,"abstract":"This paper aims to investigate the use of emojis to contextualize mourning on Twitter. Specifically, we seek to determine (i) whether an emoji is sufficient to contextualize expressions of grief; (ii) which emojis most accurately represent mourning; (iii) whether only words are used to contextualize mourning; (iv) which words are used to characterize mourning in tweets; and, (v) if there are differences in the expression of mourning in different languages. For this, we use a multi-stage method to conduct a comprehensive analysis of the manifestations of grieving behavior on Twitter, and created machine learning models to classify expressions of mourning in tweets. The main contributions from this work are (1) a gold standard of manually annotated mourning tweets; (2) classification models produced using machine learning ensemble methods and BERT contextual embeddings; and, (3) an extensive analysis of our findings opening up opportunities for new research. The results of this paper reveal emojis alone are insufficient for identifying expressions of mourning in tweets, and the combination of both emojis and words is the most effective strategy for contextualizing mourning online -- the models achieved the 84.8%-97% F1 score in all datasets. Although words alone are capable of characterizing mourning contexts correctly, the English vocabulary is limited, and the contribution of RIP - the abbreviation for \"rest in peace'' - is highly decisive. Our results have also shown that the most relevant emojis for this context were emotional ones, such as includegraphics[width=1em]twitter_brokenheart.png, and emojis are used in a uniform fashion in both Spanish and English.","PeriodicalId":325072,"journal":{"name":"Proceedings of the 32nd ACM Conference on Hypertext and Social Media","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122546184","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}
Aaron Necaise, Aneka Williams, Hana Vrzakova, M. J. Amon
{"title":"Regularity Versus Novelty of Users' Multimodal Comment Patterns and Dynamics as Markers of Social Media Radicalization","authors":"Aaron Necaise, Aneka Williams, Hana Vrzakova, M. J. Amon","doi":"10.1145/3465336.3475095","DOIUrl":"https://doi.org/10.1145/3465336.3475095","url":null,"abstract":"Although the internet is a means for disseminating information and facilitating social interactions, these benefits are limited due to individuals' propensity for engaging within a narrow range of communities that share similar beliefs. A portion of these online communities facilitate radicalist viewpoints, including toward marginalized populations, contributing to misbehavior and exacerbating social inequalities. Although a variety of theories propose to explain the processes of online radicalization, less work has empirically examined how users' communication patterns change over time, especially in terms of novelty versus regularity of user comment features. The present research demonstrates a new modeling approach for examining the extent to which low-level, multimodal comment patterns evolve as users communicate within a Reddit forum well-known for its extreme misogynism. Our results confirm that low-level comment patterns predict high-level features of radicalization, aligning with theory on attitude polarization and contributing to literature on detection and interventions to mitigate extremism.","PeriodicalId":325072,"journal":{"name":"Proceedings of the 32nd ACM Conference on Hypertext and Social Media","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128095069","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}
Zahra Nouri, U. Gadiraju, G. Engels, Henning Wachsmuth
{"title":"What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing","authors":"Zahra Nouri, U. Gadiraju, G. Engels, Henning Wachsmuth","doi":"10.1145/3465336.3475109","DOIUrl":"https://doi.org/10.1145/3465336.3475109","url":null,"abstract":"Designing tasks clearly to facilitate accurate task completion is a challenging endeavor for requesters on crowdsourcing platforms. Prior research shows that inexperienced requesters fail to write clear and complete task descriptions which directly leads to low quality submissions from workers. By complementing existing works that have aimed to address this challenge, in this paper we study whether clarity flaws in task descriptions can be identified automatically using natural language processing methods. We identify and synthesize seven clarity flaws in task descriptions that are grounded in relevant literature. We build both BERT-based and feature-based binary classifiers, in order to study the extent to which clarity flaws in task descriptions can be computationally assessed, and understand textual properties of descriptions that affect task clarity. Through a crowdsourced study, we collect annotations of clarity flaws in 1332 real task descriptions. Using this dataset, we evaluate several configurations of the classifiers. Our results indicate that nearly all the clarity flaws in task descriptions can be assessed reasonably by the classifiers. We found that the content, style, and readability of tasks descriptions are particularly important in shaping their clarity. This work has important implications on the design of tools to help requesters in improving task clarity on crowdsourcing platforms. Flaw-specific properties can provide for valuable guidance in improving task descriptions.","PeriodicalId":325072,"journal":{"name":"Proceedings of the 32nd ACM Conference on Hypertext and Social Media","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122727265","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}
B. Signer, Reinout Roels, R. van Barlingen, Brent Willems
{"title":"Back to the Future: Bringing Original Hypermedia and Cross-Media Concepts to Modern Desktop Environments","authors":"B. Signer, Reinout Roels, R. van Barlingen, Brent Willems","doi":"10.1145/3465336.3475122","DOIUrl":"https://doi.org/10.1145/3465336.3475122","url":null,"abstract":"Over the last few decades, we have seen massive improvements in computing power, but nevertheless we still rely on digital documents and file systems that were originally created by mimicking the characteristics of physical storage media with all its limitations. This is quite surprising given that even before the existence of the computer, Information Science visionaries such as Vannevar Bush described more powerful information management solutions. We therefore aim to improve the way information is managed in modern desktop environments by embedding a hypermedia engine offering rich hypermedia and cross-media concepts at the level of an operating system. We discuss the resource-selector-link (RSL) hypermedia metamodel as a candidate for realising such a general hypermedia engine and highlight its flexibility based on a number of domain-specific applications that have been developed over the last two decades. The underlying content repository will no longer rely on monolithic files, but rather contain a user's data in the form of content fragments, such as snippets of text or images, which are structurally linked to form the corresponding documents, and can be reused in other documents or even shared across computers. By increasing the scope to a system-wide hypermedia engine, we have to deal with fundamental challenges related to granularity, interoperability or context resolving. We strongly believe that computing technology has evolved enough to revisit and address these challenges, laying the foundation for a wide range of innovative use cases for efficiently managing cross-media content in modern desktop environments.","PeriodicalId":325072,"journal":{"name":"Proceedings of the 32nd ACM Conference on Hypertext and Social Media","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122871122","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}
{"title":"Genre-bending on an Academic Platform: Three Creative Works on Scalar","authors":"Hannah Ackermans","doi":"10.1145/3465336.3475099","DOIUrl":"https://doi.org/10.1145/3465336.3475099","url":null,"abstract":"This paper investigates genre and media specificity of electronic literature created in Scalar. Scalar is a platform and authoring tool created specifically for humanities scholars to enable multimodal and multilinear publications. Besides scholarly work, Robert Budac's The Scalar Conspiracy [4], Steven Wingate's daddylabyrinth: a digital lyric memoir [12] and micha cárdenas' Redshift & Portalmetal [5] are all works of electronic literature created in Scalar. I demonstrate that all three of these works use Scalar to create genre-bending texts that build on and subvert the technological affordances as well as the contextual connotations that Scalar provides. The Scalar Conspiracy parodies the counter-intuitive user interface elements by making the reader investigate the text's different hidden messages. daddylabyrinth: a digital lyric memoir destabilizes the genre of the (auto)biography by promoting documentation and research while continuously showing how these processes fall short during the writing and reading process. Redshift & Portalmetal favors experience over documentation to create a work that is both immersive and theory-building. These Scalar fictions are characterized by the premise that the platform's academic context strengthens the narrative. Researching the multimodality and academic context as integral parts of the narrative structure opens up the opportunity to reckon with the platform-specificity across genres.","PeriodicalId":325072,"journal":{"name":"Proceedings of the 32nd ACM Conference on Hypertext and Social Media","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134062170","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}
{"title":"Towards an Archive of the Future: Reconstructing Ireland's Lost History through the Beyond 2022 Project","authors":"Peter Crooks, Gary Munnelly","doi":"10.1145/3465336.3475090","DOIUrl":"https://doi.org/10.1145/3465336.3475090","url":null,"abstract":"In 1922, the 'Record Treasury' of the Public Record Office of Ireland in Dublin was destroyed in the opening engagement of Ireland's Civil War. The Treasury contained millions of historical documents filling 100,000 square feet of shelving organised into 5,500 series of records accumulated over seven centuries. It was destroyed in one afternoon. Beyond 2022 is an international collaborative research project based at the ADAPT Centre, Trinity College Dublin, and funded by the Government of Ireland. We are working to create a virtual reimagining of this lost national archive. Many millions of words from destroyed documents will be linked and reassembled from copies, transcripts and other records scattered among the collections of our archival partners. We will bring together this rich array of replacement items within an immersive 3-D reconstruction of the destroyed building. In this keynote address, we will discuss the Digital Humanities and Knowledge Engineering challenges presented by the project, and also reflect on how this reimagining of a lost archive will provide deeper search and discoverability than was possible one hundred years ago when the archive was still in existence.","PeriodicalId":325072,"journal":{"name":"Proceedings of the 32nd ACM Conference on Hypertext and Social Media","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134461900","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}