Pub Date : 2023-06-02DOI: 10.1609/icwsm.v17i1.22218
Shao Yi Liaw, Fan Huang, Fabricio Benevenuto, Haewoon Kwak, Jisun An
Conspiracy theories are widely propagated on social media. Among various social media services, YouTube is one of the most influential sources of news and entertainment. This paper seeks to develop a dataset, YOUNICON, to enable researchers to perform conspiracy theory detection as well as classification of videos with conspiracy theories into different topics. YOUNICON is a dataset with a large collection of videos from suspicious channels that were identified to contain conspiracy theories in a previous study. Overall, YOUNICON will enable researchers to study trends in conspiracy theories and understand how individuals can interact with the conspiracy theory producing community or channel. Our data is available at: https://doi.org/10.5281/zenodo.7466262.
{"title":"YouNICon: YouTube’s CommuNIty of Conspiracy Videos","authors":"Shao Yi Liaw, Fan Huang, Fabricio Benevenuto, Haewoon Kwak, Jisun An","doi":"10.1609/icwsm.v17i1.22218","DOIUrl":"https://doi.org/10.1609/icwsm.v17i1.22218","url":null,"abstract":"Conspiracy theories are widely propagated on social media. Among various social media services, YouTube is one of the most influential sources of news and entertainment. This paper seeks to develop a dataset, YOUNICON, to enable researchers to perform conspiracy theory detection as well as classification of videos with conspiracy theories into different topics. YOUNICON is a dataset with a large collection of videos from suspicious channels that were identified to contain conspiracy theories in a previous study. Overall, YOUNICON will enable researchers to study trends in conspiracy theories and understand how individuals can interact with the conspiracy theory producing community or channel. Our data is available at: https://doi.org/10.5281/zenodo.7466262.","PeriodicalId":338112,"journal":{"name":"Proceedings of the International AAAI Conference on Web and Social Media","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136041293","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}
Pub Date : 2023-06-02DOI: 10.1609/icwsm.v17i1.22199
Yulin Yu, Pui Yin Cheung, Yong-Yeol Ahn, Paramveer S. Dhillon
How does our society appreciate the uniqueness of cultural products? This fundamental puzzle has intrigued scholars in many fields, including psychology, sociology, anthropology, and marketing. It has been theorized that cultural products that balance familiarity and novelty are more likely to become popular. However, a cultural product's novelty is typically multifaceted. This paper uses songs as a case study to study the multiple facets of uniqueness and their relationship with success. We first unpack the multiple facets of a song's novelty or uniqueness and, next, measure its impact on a song's popularity. We employ a series of statistical models to study the relationship between a song's popularity and novelty associated with its lyrics, chord progressions, or audio properties. Our analyses performed on a dataset of over fifty thousand songs find a consistently negative association between all types of song novelty and popularity. Overall we found a song's lyrics uniqueness to have the most significant association with its popularity. However, audio uniqueness was the strongest predictor of a song's popularity, conditional on the song's genre. We further found the theme and repetitiveness of a song's lyrics to mediate the relationship between the song's popularity and novelty. Broadly, our results contradict the "optimal distinctiveness theory'' (balance between novelty and familiarity) and call for an investigation into the multiple dimensions along which a cultural product's uniqueness could manifest.
{"title":"Unique in What Sense? Heterogeneous Relationships between Multiple Types of Uniqueness and Popularity in Music","authors":"Yulin Yu, Pui Yin Cheung, Yong-Yeol Ahn, Paramveer S. Dhillon","doi":"10.1609/icwsm.v17i1.22199","DOIUrl":"https://doi.org/10.1609/icwsm.v17i1.22199","url":null,"abstract":"How does our society appreciate the uniqueness of cultural products? This fundamental puzzle has intrigued scholars in many fields, including psychology, sociology, anthropology, and marketing. It has been theorized that cultural products that balance familiarity and novelty are more likely to become popular. However, a cultural product's novelty is typically multifaceted. This paper uses songs as a case study to study the multiple facets of uniqueness and their relationship with success. We first unpack the multiple facets of a song's novelty or uniqueness and, next, measure its impact on a song's popularity. We employ a series of statistical models to study the relationship between a song's popularity and novelty associated with its lyrics, chord progressions, or audio properties. Our analyses performed on a dataset of over fifty thousand songs find a consistently negative association between all types of song novelty and popularity. Overall we found a song's lyrics uniqueness to have the most significant association with its popularity. However, audio uniqueness was the strongest predictor of a song's popularity, conditional on the song's genre. We further found the theme and repetitiveness of a song's lyrics to mediate the relationship between the song's popularity and novelty. Broadly, our results contradict the \"optimal distinctiveness theory'' (balance between novelty and familiarity) and call for an investigation into the multiple dimensions along which a cultural product's uniqueness could manifest.","PeriodicalId":338112,"journal":{"name":"Proceedings of the International AAAI Conference on Web and Social Media","volume":"510 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136041294","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}
Pub Date : 2023-06-02DOI: 10.1609/icwsm.v17i1.22124
Dominik Bär, Nicolas Pröllochs, Stefan Feuerriegel
The social media platform "Parler'' has emerged into a prominent fringe community where a significant part of the user base are self-reported supporters of QAnon, a far-right conspiracy theory alleging that a cabal of elites controls global politics. QAnon is considered to have had an influential role in the public discourse during the 2020 U.S. presidential election. However, little is known about QAnon supporters on Parler and what sets them aside from other users. Building up on social identity theory, we aim to profile the characteristics of QAnon supporters on Parler. We analyze a large-scale dataset with more than 600,000 profiles of English-speaking users on Parler. Based on users' profiles, posts, and comments, we then extract a comprehensive set of user features, linguistic features, network features, and content features. This allows us to perform user profiling and understand to what extent these features discriminate between QAnon and non-QAnon supporters on Parler. Our analysis is three-fold: (1) We quantify the number of QAnon supporters on Parler, finding that 34,913 users (5.5% of all users) openly report supporting the conspiracy. (2) We examine differences between QAnon vs. non-QAnon supporters. We find that QAnon supporters differ statistically significantly from non-QAnon supporters across multiple dimensions. For example, they have, on average, a larger number of followers, followees, and posts, and thus have a large impact on the Parler network. (3) We use machine learning to identify which user characteristics discriminate QAnon from non-QAnon supporters. We find that user features, linguistic features, network features, and content features, can - to a large extent - discriminate QAnon vs. non-QAnon supporters on Parler. In particular, we find that user features are highly discriminatory, followed by content features and linguistic features.
{"title":"Finding Qs: Profiling QAnon Supporters on Parler","authors":"Dominik Bär, Nicolas Pröllochs, Stefan Feuerriegel","doi":"10.1609/icwsm.v17i1.22124","DOIUrl":"https://doi.org/10.1609/icwsm.v17i1.22124","url":null,"abstract":"The social media platform \"Parler'' has emerged into a prominent fringe community where a significant part of the user base are self-reported supporters of QAnon, a far-right conspiracy theory alleging that a cabal of elites controls global politics. QAnon is considered to have had an influential role in the public discourse during the 2020 U.S. presidential election. However, little is known about QAnon supporters on Parler and what sets them aside from other users. Building up on social identity theory, we aim to profile the characteristics of QAnon supporters on Parler. We analyze a large-scale dataset with more than 600,000 profiles of English-speaking users on Parler. Based on users' profiles, posts, and comments, we then extract a comprehensive set of user features, linguistic features, network features, and content features. This allows us to perform user profiling and understand to what extent these features discriminate between QAnon and non-QAnon supporters on Parler. Our analysis is three-fold: (1) We quantify the number of QAnon supporters on Parler, finding that 34,913 users (5.5% of all users) openly report supporting the conspiracy. (2) We examine differences between QAnon vs. non-QAnon supporters. We find that QAnon supporters differ statistically significantly from non-QAnon supporters across multiple dimensions. For example, they have, on average, a larger number of followers, followees, and posts, and thus have a large impact on the Parler network. (3) We use machine learning to identify which user characteristics discriminate QAnon from non-QAnon supporters. We find that user features, linguistic features, network features, and content features, can - to a large extent - discriminate QAnon vs. non-QAnon supporters on Parler. In particular, we find that user features are highly discriminatory, followed by content features and linguistic features.","PeriodicalId":338112,"journal":{"name":"Proceedings of the International AAAI Conference on Web and Social Media","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135911346","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}
Pub Date : 2023-06-02DOI: 10.1609/icwsm.v17i1.22179
Lynnette Hui Xian Ng, Kathleen M. Carley
Despite rapid development, current bot detection models still face challenges in dealing with incomplete data and cross-platform applications. In this paper, we propose BotBuster, a social bot detector built with the concept of a mixture of experts approach. Each expert is trained to analyze a portion of account information, e.g. username, and are combined to estimate the probability that the account is a bot. Experiments on 10 Twitter datasets show that BotBuster outperforms popular bot-detection baselines (avg F1=73.54 vs avg F1=45.12). This is accompanied with F1=60.04 on a Reddit dataset and F1=60.92 on an external evaluation set. Further analysis shows that only 36 posts is required for a stable bot classification. Investigation shows that bot post features have changed across the years and can be difficult to differentiate from human features, making bot detection a difficult and ongoing problem.
尽管发展迅速，但目前的机器人检测模型在处理不完整数据和跨平台应用方面仍然面临挑战。在本文中，我们提出BotBuster，一个基于混合专家方法的概念构建的社交机器人检测器。每个专家都经过培训，可以分析一部分帐户信息，例如用户名，并结合起来估计该帐户是机器人的概率。在10个Twitter数据集上的实验表明，BotBuster优于流行的机器人检测基线(avg F1=73.54 vs avg F1=45.12)。在Reddit数据集上F1=60.04，在外部评估集上F1=60.92。进一步分析表明，稳定的bot分类只需要36个帖子。调查显示，多年来，机器人帖子的特征已经发生了变化，很难与人类特征区分开来，这使得机器人检测成为一个困难且持续存在的问题。
{"title":"BotBuster: Multi-Platform Bot Detection Using a Mixture of Experts","authors":"Lynnette Hui Xian Ng, Kathleen M. Carley","doi":"10.1609/icwsm.v17i1.22179","DOIUrl":"https://doi.org/10.1609/icwsm.v17i1.22179","url":null,"abstract":"Despite rapid development, current bot detection models still face challenges in dealing with incomplete data and cross-platform applications. In this paper, we propose BotBuster, a social bot detector built with the concept of a mixture of experts approach. Each expert is trained to analyze a portion of account information, e.g. username, and are combined to estimate the probability that the account is a bot. Experiments on 10 Twitter datasets show that BotBuster outperforms popular bot-detection baselines (avg F1=73.54 vs avg F1=45.12). This is accompanied with F1=60.04 on a Reddit dataset and F1=60.92 on an external evaluation set. Further analysis shows that only 36 posts is required for a stable bot classification. Investigation shows that bot post features have changed across the years and can be difficult to differentiate from human features, making bot detection a difficult and ongoing problem.","PeriodicalId":338112,"journal":{"name":"Proceedings of the International AAAI Conference on Web and Social Media","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135912559","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}
Pub Date : 2021-09-25DOI: 10.1609/icwsm.v2i1.18604
Noor F. Ali-Hasan
The use of social technologies is becoming ubiquitous in the lives of average computer users. However, social media has yet to infiltrate users' television experiences. This paper presents the findings of an exploratory study examining social scenarios for TV. Eleven participants took part in the three-part study that included in-home field visits, a diary study of participants' daily usage of TV and social media, and participatory design sessions. During the participatory design sessions, participants evaluated and discussed several paper wireframes of potential social TV applications. Overall, participants responded to most social TV concepts with excitement and enthusiasm, but were leery of scenarios that they felt violated their privacy.
{"title":"Exploring Social Media Scenarios for the Television","authors":"Noor F. Ali-Hasan","doi":"10.1609/icwsm.v2i1.18604","DOIUrl":"https://doi.org/10.1609/icwsm.v2i1.18604","url":null,"abstract":"The use of social technologies is becoming ubiquitous in the lives of average computer users. However, social media has yet to infiltrate users' television experiences. This paper presents the findings of an exploratory study examining social scenarios for TV. Eleven participants took part in the three-part study that included in-home field visits, a diary study of participants' daily usage of TV and social media, and participatory design sessions. During the participatory design sessions, participants evaluated and discussed several paper wireframes of potential social TV applications. Overall, participants responded to most social TV concepts with excitement and enthusiasm, but were leery of scenarios that they felt violated their privacy.","PeriodicalId":338112,"journal":{"name":"Proceedings of the International AAAI Conference on Web and Social Media","volume":"176 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120959789","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}
Pub Date : 2021-09-25DOI: 10.1609/icwsm.v2i1.18619
Jason S Kessler
The research described here is part of a larger project with the objective of determining if a writer believes a proposition to be true or false. This task requires a deep understanding of a proposition's semantic context, which is far beyond NLP's state of the art. In light of this difficulty, this paper presents a shallow semantic framework that addresses the sub-problem of finding a proposition's truth-value at the sentence level. The framework consists of several classes of linguistic elements that, when linked to a proposition through specific lexico-syntactic connectors, change its truth-value. A pilot evaluation of a system implementing this framework yields promising results.
{"title":"Polling the Blogosphere: A Rule-Based Approach to Belief Classification","authors":"Jason S Kessler","doi":"10.1609/icwsm.v2i1.18619","DOIUrl":"https://doi.org/10.1609/icwsm.v2i1.18619","url":null,"abstract":"The research described here is part of a larger project with the objective of determining if a writer believes a proposition to be true or false. This task requires a deep understanding of a proposition's semantic context, which is far beyond NLP's state of the art. In light of this difficulty, this paper presents a shallow semantic framework that addresses the sub-problem of finding a proposition's truth-value at the sentence level. The framework consists of several classes of linguistic elements that, when linked to a proposition through specific lexico-syntactic connectors, change its truth-value. A pilot evaluation of a system implementing this framework yields promising results.","PeriodicalId":338112,"journal":{"name":"Proceedings of the International AAAI Conference on Web and Social Media","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124739519","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}
Pub Date : 2021-09-25DOI: 10.1609/icwsm.v2i1.18642
Linda M. Gallant, Gloria M. Boone
Individuals are active audience members that use Internet-based social media technologies to create and negotiate social action in online spaces. Communicative informatics is the key to constructing, describing or critiquing social media. Communicative informatics is the discovery of the audience, text/image, technology, negotiated place relationships that create symbolic meaning. Four propositions focus on the communication of the audience: 1) the audience is active; 2) the audience is creative; 3) the audience interacts with technology and 4) place is negotiated in online communication.
{"title":"Communicative Informatics: A Social Media Perspective for Online Communities","authors":"Linda M. Gallant, Gloria M. Boone","doi":"10.1609/icwsm.v2i1.18642","DOIUrl":"https://doi.org/10.1609/icwsm.v2i1.18642","url":null,"abstract":"Individuals are active audience members that use Internet-based social media technologies to create and negotiate social action in online spaces. Communicative informatics is the key to constructing, describing or critiquing social media. Communicative informatics is the discovery of the audience, text/image, technology, negotiated place relationships that create symbolic meaning. Four propositions focus on the communication of the audience: 1) the audience is active; 2) the audience is creative; 3) the audience interacts with technology and 4) place is negotiated in online communication.","PeriodicalId":338112,"journal":{"name":"Proceedings of the International AAAI Conference on Web and Social Media","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130756479","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}
Pub Date : 2021-09-25DOI: 10.1609/icwsm.v2i1.18621
Ramesh Nallapati, William W. Cohen
In this work, we address the twin problems of unsupervised topic discovery and estimation of topic specific influence of blogs. We propose a new model that can be used to provide a user with highly influential blog postings on the topic of the user's interest. We adopt the framework of an unsupervised model called Latent Dirichlet Allocation, known for its effectiveness in topic discovery. An extension of this model, which we call Link-LDA, defines a generative model for hyperlinks and thereby models topic specific influence of documents, the problem of our interest. However, this model does not exploit the topical relationship between the documents on either side of a hyperlink, i.e., the notion that documents tend to link to other documents on the same topic. We propose a new model, called Link-PLSA-LDA, that combines PLSA and LDA into a single framework, and explicitly models the topical relationship between the linking and the linked document. The output of the new model on blog data reveals very interesting visualizations of topics and influential blogs on each topic. We also perform quantitative evaluation of the model using log-likelihood of unseen data and on the task of link prediction. Both experiments show that that the new model performs better, suggesting its superiority over Link-LDA in modeling topics and topic specific influence of blogs.
{"title":"Link-PLSA-LDA: A New Unsupervised Model for Topics and Influence of Blogs","authors":"Ramesh Nallapati, William W. Cohen","doi":"10.1609/icwsm.v2i1.18621","DOIUrl":"https://doi.org/10.1609/icwsm.v2i1.18621","url":null,"abstract":"In this work, we address the twin problems of unsupervised topic discovery and estimation of topic specific influence of blogs. We propose a new model that can be used to provide a user with highly influential blog postings on the topic of the user's interest. We adopt the framework of an unsupervised model called Latent Dirichlet Allocation, known for its effectiveness in topic discovery. An extension of this model, which we call Link-LDA, defines a generative model for hyperlinks and thereby models topic specific influence of documents, the problem of our interest. However, this model does not exploit the topical relationship between the documents on either side of a hyperlink, i.e., the notion that documents tend to link to other documents on the same topic. We propose a new model, called Link-PLSA-LDA, that combines PLSA and LDA into a single framework, and explicitly models the topical relationship between the linking and the linked document. The output of the new model on blog data reveals very interesting visualizations of topics and influential blogs on each topic. We also perform quantitative evaluation of the model using log-likelihood of unseen data and on the task of link prediction. Both experiments show that that the new model performs better, suggesting its superiority over Link-LDA in modeling topics and topic specific influence of blogs.","PeriodicalId":338112,"journal":{"name":"Proceedings of the International AAAI Conference on Web and Social Media","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114832710","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}
Pub Date : 2021-09-25DOI: 10.1609/icwsm.v2i1.18652
Thomas M. Lento, Eric Gleave, Marc A. Smith, Howard T. Welser
This study investigates how heavily active contributors affect recruitment and retention in online social systems. We find that core enthusiasts are more successful recruiters, their recruits are more likely to become enthusiasts, and interacting with enthusiasts makes users less likely to exit the system. We also find evidence that strong dyadic ties between non-enthusiasts help extend active careers in online social systems. Implications include considerations for community growth and retention based on the influence of these core users.
{"title":"Some Users Pack a Wallop: Measuring the Impact of Core Users on the Participation of Others in Online Social Systems","authors":"Thomas M. Lento, Eric Gleave, Marc A. Smith, Howard T. Welser","doi":"10.1609/icwsm.v2i1.18652","DOIUrl":"https://doi.org/10.1609/icwsm.v2i1.18652","url":null,"abstract":"This study investigates how heavily active contributors affect recruitment and retention in online social systems. We find that core enthusiasts are more successful recruiters, their recruits are more likely to become enthusiasts, and interacting with enthusiasts makes users less likely to exit the system. We also find evidence that strong dyadic ties between non-enthusiasts help extend active careers in online social systems. Implications include considerations for community growth and retention based on the influence of these core users.","PeriodicalId":338112,"journal":{"name":"Proceedings of the International AAAI Conference on Web and Social Media","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116326124","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}
Pub Date : 2021-09-25DOI: 10.1609/icwsm.v2i1.18645
Indratmo, Julita Vassileva
We developed and evaluated a visualization tool for browsing individual blog archives. In our study, we solicited qualitative feedback from the participants to explore the reasons behind their usability ratings. This feedback reveals factors that are deemed important in selecting entries to read, and adds to the understanding of blogging practices. Based on our analysis, we propose two design principles to complement the current blog interfaces: (1) A blog should provide a rich overview of its content to ease information exploration; and (2) A blog should utilize social interaction history to help users find potentially useful entries.
{"title":"iBlogVis: An Interactive Blog Visualization Tool","authors":"Indratmo, Julita Vassileva","doi":"10.1609/icwsm.v2i1.18645","DOIUrl":"https://doi.org/10.1609/icwsm.v2i1.18645","url":null,"abstract":"We developed and evaluated a visualization tool for browsing individual blog archives. In our study, we solicited qualitative feedback from the participants to explore the reasons behind their usability ratings. This feedback reveals factors that are deemed important in selecting entries to read, and adds to the understanding of blogging practices. Based on our analysis, we propose two design principles to complement the current blog interfaces: (1) A blog should provide a rich overview of its content to ease information exploration; and (2) A blog should utilize social interaction history to help users find potentially useful entries.","PeriodicalId":338112,"journal":{"name":"Proceedings of the International AAAI Conference on Web and Social Media","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123231617","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：