Proceedings of the 31st ACM Conference on Hypertext and Social Media最新文献_第3页

Tell Me What You Want: Embedding Narratives for Movie Recommendations 告诉我你想要什么:为电影推荐嵌入叙事

Proceedings of the 31st ACM Conference on Hypertext and Social Media Pub Date : 2020-07-13 DOI: 10.1145/3372923.3404818

Lukas Eberhard, Simon Walk, D. Helic

{"title":"Tell Me What You Want: Embedding Narratives for Movie Recommendations","authors":"Lukas Eberhard, Simon Walk, D. Helic","doi":"10.1145/3372923.3404818","DOIUrl":"https://doi.org/10.1145/3372923.3404818","url":null,"abstract":"Recommender systems are efficient exploration tools providing their users with valuable suggestions about items, such as products or movies. However, in scenarios where users have more specific ideas about what they are looking for (e.g., they provide describing narratives, such as \"Movies with minimal story, but incredible atmosphere, such as No Country for Old Men\"), traditional recommender systems struggle to provide relevant suggestions. In this paper, we study this problem by investigating a large collection of such narratives from the movie domain. We start by empirically analyzing a dataset containing free-text narratives representing movie suggestion requests from reddit users as well as community suggestions to those requests. We find that community suggestions are frequently more diverse than requests, making a recommendation task a challenging one. In a prediction experiment, we use embedding algorithms to assess the importance of request features including movie descriptions, genres, and plot keywords, by computing recommendations. Our findings suggest that, in our dataset, positive movies and keywords have the strongest, whereas negative movie features have the weakest predictive power. We strongly believe that our new insights into narratives for recommender systems represent an important stepping stone towards novel applications, such as interactive recommender applications.","PeriodicalId":389616,"journal":{"name":"Proceedings of the 31st ACM Conference on Hypertext and Social Media","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121318364","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 Sociolinguistic Route to the Characterization and Detection of the Credibility of Events on Twitter 推特事件可信度表征与检测的社会语言学路径

Proceedings of the 31st ACM Conference on Hypertext and Social Media Pub Date : 2020-07-13 DOI: 10.1145/3372923.3404795

Jasabanta Patro, Pushpendra Kumar Singh Rathore

{"title":"A Sociolinguistic Route to the Characterization and Detection of the Credibility of Events on Twitter","authors":"Jasabanta Patro, Pushpendra Kumar Singh Rathore","doi":"10.1145/3372923.3404795","DOIUrl":"https://doi.org/10.1145/3372923.3404795","url":null,"abstract":"Although Twitter constitutes as one of the primary sources of real-time news with users acting as the sensors updating the content from all across the globe, yet the spread of rumours via Twitter is becoming an increasingly alarming issue and is known to have caused significant damage already. We propose a credibility analysis approach based on the linguistic structure of the tweets. We not only characterize the Twitter events but also predict their perceived credibility of them by a novel deep learning architecture. We use the huge CREDBANK data to conduct our experiments. Some of our exciting findings are that standard LIWC categories like 'negate', 'discrep', 'cogmech', 'swear' and the Empath categories like 'hate', 'poor', 'government', 'worship' and 'swearing-terms' correlate negatively with the credibility of events. While some of our results resonate with the earlier literature others represent novel insights of the fake and legitimate twitter events. Using the above observations and the current deep learning architecture we predict the credibility of an event (a four-class classification problem in our case) with an accuracy of 0.54 that improves the best-known state-of-the-art (current accuracy 0.43) by ~ 26%. A fascinating observation is that even by looking at the first few tweets of an event, it is possible to make the prediction almost as accurate as in the case where the entire volume of tweets is observed.","PeriodicalId":389616,"journal":{"name":"Proceedings of the 31st ACM Conference on Hypertext and Social Media","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121509215","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

How Does Team Composition Affect Knowledge Gain of Users in Collaborative Web Search? 团队构成如何影响协同网络搜索中用户的知识获取?

Proceedings of the 31st ACM Conference on Hypertext and Social Media Pub Date : 2020-07-13 DOI: 10.1145/3372923.3404784

Luyan Xu, Xuan Zhou, U. Gadiraju

{"title":"How Does Team Composition Affect Knowledge Gain of Users in Collaborative Web Search?","authors":"Luyan Xu, Xuan Zhou, U. Gadiraju","doi":"10.1145/3372923.3404784","DOIUrl":"https://doi.org/10.1145/3372923.3404784","url":null,"abstract":"Studies in searching as learning (SAL) have revealed that user knowledge gain not only manifests over a long-term learning period, but also occurs in single short-term web search sessions. Though prior works have shown that the knowledge gain of collaborators can be influenced by user demographics and searching strategies in long-term collaborative learning, little is known about the effect of these factors on user knowledge gain in short-term collaborative web search. In this paper, we present a study addressing the knowledge gain of user pairs in single collaborative web search sessions. Using crowdsourcing we recruited 454 unique users (227 random pairs), who then collaboratively worked on informational search tasks spanning 10 different topics and information needs. We investigated how users' demographics and traits, and the interaction between these factors could influence their knowledge gain. We found that in contrast to offline collaboration cases, user demographics such as gender, age, etc. do not significantly effect users' knowledge gain in collaborative web search sessions. Instead, our results highlight the presence of labor division of queries and particular interaction patterns in communication that facilitate knowledge gain in user pairs. Based on these findings, we propose a multiple linear regression model to predict the knowledge gain of users in collaborative web search sessions from the perspective of team composition.","PeriodicalId":389616,"journal":{"name":"Proceedings of the 31st ACM Conference on Hypertext and Social Media","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121648237","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

3rd Workshop on Human Factors in Hypertext (HUMAN'20) 第三届超文本中的人为因素研讨会(Human '20)

Proceedings of the 31st ACM Conference on Hypertext and Social Media Pub Date : 2020-07-13 DOI: 10.1145/3372923.3405431

Claus Atzenbeck, J. Rubart

引用次数: 1

Understanding Targeted Video-Ads in Children's Content 理解儿童内容中的定向视频广告

Proceedings of the 31st ACM Conference on Hypertext and Social Media Pub Date : 2020-07-13 DOI: 10.1145/3372923.3404787

F. Figueiredo, Felipe Giori, Guilherme Soares, Mariana Arantes, J. Almeida, Fabrício Benevenuto

{"title":"Understanding Targeted Video-Ads in Children's Content","authors":"F. Figueiredo, Felipe Giori, Guilherme Soares, Mariana Arantes, J. Almeida, Fabrício Benevenuto","doi":"10.1145/3372923.3404787","DOIUrl":"https://doi.org/10.1145/3372923.3404787","url":null,"abstract":"As the volume of online video entertainment via streaming increases, ever so more are users targeted by online advertisement algorithms. Nevertheless, this rise in targeting and revenue does not come without any concerns. That is, even though the online advertising business model has is very successful, nowadays, rising societal concerns regarding the ethics and extent to which such algorithms agree with the laws of different countries are also present. Motivated by the dichotomy above, we here explore how targeted video-ads meet the regulatory policies regarding children advertising in Brazil and Canada. To perform our study, we create synthetic user personas that watch YouTube videos daily. Our personas are tailored to stream children's content while controlling for several variables (e.g., gender, country, and type of content streamed). With the data gathered, our analyses reveal statistical evidence of algorithmic targeting in videos geared towards children. Also, some of the advertised products (e.g., alcoholic beverages and fast-food) go directly against the regulations of the studied countries. With advertisements being matched to users by machine learning algorithms, it is impossible to state whether regulations are not followed on purpose (e.g., advertisers gaming the system). Nevertheless, our findings and discussion do raise a flag that regulations may not be sufficient, and content providers may still need to audit systems to meet the regulations.","PeriodicalId":389616,"journal":{"name":"Proceedings of the 31st ACM Conference on Hypertext and Social Media","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123644657","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

Bad Character: Who do We Want our Hypertexts to Be? 坏角色:我们希望我们的超文本是谁?

Proceedings of the 31st ACM Conference on Hypertext and Social Media Pub Date : 2020-07-13 DOI: 10.1145/3372923.3404777

M. Bernstein

引用次数: 3

Mediation as Calibration: A Framework for Evaluating the Author/Reader Relation 中介作为校准:一个评估作者/读者关系的框架

Proceedings of the 31st ACM Conference on Hypertext and Social Media Pub Date : 2020-07-13 DOI: 10.1145/3372923.3404789

A. Antonini, Samuel Brooker

引用次数: 5

Learning about Queer Representation through Mods: Reviewing Past Challenges and Outlining Ideas About Future Approaches 通过模态学习酷儿表现:回顾过去的挑战并概述未来方法的想法

Proceedings of the 31st ACM Conference on Hypertext and Social Media Pub Date : 2020-07-13 DOI: 10.1145/3372923.3404780

K. Howard

{"title":"Learning about Queer Representation through Mods: Reviewing Past Challenges and Outlining Ideas About Future Approaches","authors":"K. Howard","doi":"10.1145/3372923.3404780","DOIUrl":"https://doi.org/10.1145/3372923.3404780","url":null,"abstract":"In this paper I outline an idea that I am researching more fully in my PhD dissertation: using modification of video games as an educational method to explore queer representation. This paper primarily focuses on educational concerns related to that approach: I first review discussions about the challenges surrounding game-based learning approaches and claim that some common points of skepticism in these discussions actually highlight the effectiveness of games for learning about queer representation. I also suggest that, as a genre, choice-based interactive fiction is ideal for exploratory learning about queer representation in comparison to other kinds of games. I then analyze educational uses of video game modification, noting that one of the most common approaches is educators modifying popular games for the classroom. I claim that approach could work especially well as a way to explore problems with representation in video games. I close the article with a short discussion about expanding upon this approach by building an easily-modifiable interactive fiction game to address issues with portrayals of queerness in mainstream games, a method I examine more fully in my PhD dissertation and through an associated digital game prototype. Overall, I argue that interactive fiction works are very well-suited to dealing with issues of representation and that modifiable interactive fiction games are an effective way to learn more about problems with representation in video games.","PeriodicalId":389616,"journal":{"name":"Proceedings of the 31st ACM Conference on Hypertext and Social Media","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122632111","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

Simulating the Impact of Recommender Systems on the Evolution of Collective Users' Choices 模拟推荐系统对集体用户选择演化的影响

Proceedings of the 31st ACM Conference on Hypertext and Social Media Pub Date : 2020-07-13 DOI: 10.1145/3372923.3404812

Naieme Hazrati, Mehdi Elahi, F. Ricci

引用次数: 11

Climates of Change: An Online Exhibition of Creative Work 气候变化:创意作品在线展览

Proceedings of the 31st ACM Conference on Hypertext and Social Media Pub Date : 2020-07-13 DOI: 10.1145/3372923.3404861

Jason Nelson, Anastasia Salter

{"title":"Climates of Change: An Online Exhibition of Creative Work","authors":"Jason Nelson, Anastasia Salter","doi":"10.1145/3372923.3404861","DOIUrl":"https://doi.org/10.1145/3372923.3404861","url":null,"abstract":"Given the global state of crisis, this year's exhibition was migrated, and a new call was distributed for online works designed to use hypertext to drive engagement with the current challenges. The curators distributed a call for works responding to the overwhelming \"climates of change,\" with a particular emphasis on the ongoing environmental crisis. Thinking globally can be overwhelming: thus, this exhibition asks artists and viewers to engage with these global concerns through the lens of local and the personal. The exhibit features works that are brief and poetic; works that engage with moments and personal challenges; works that respond to local challenges and warnings for the future that is already here. The curators welcomed works positioned through the lens of the current moment; works that challenge and inspire us; and works that call out for reflection and change. The curators particularly encouraged those submitting to draw on personal experiences or connections or understandings about climate change, the impacts, causes and effects. Pieces might also engage with how that understanding is changing every day under our growing collective challenges.","PeriodicalId":389616,"journal":{"name":"Proceedings of the 31st ACM Conference on Hypertext and Social Media","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123063801","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