URL shortener services today have come to play an important role in our social media landscape. They direct user attention and disseminate information in online social media such as Twitter or Facebook. Shortener services typically provide short URLs in exchange for long URLs. These short URLs can then be shared and diffused by users via online social media, e-mail or other forms of electronic communication. When another user clicks on the shortened URL, she will be redirected to the underlying long URL. Shortened URLs can serve many legitimate purposes, such as click tracking, but can also serve illicit behavior such as fraud, deceit and spam. Although usage of URL shortener services today is ubiquituous, our research community knows little about how exactly these services are used and what purposes they serve. In this paper, we study usage logs of a URL shortener service that has been operated by our group for more than a year. We expose the extent of spamming taking place in our logs, and provide first insights into the planetary-scale of this problem. Our results are relevant for researchers and engineers interested in understanding the emerging phenomenon and dangers of spamming via URL shortener services.
{"title":"Short links under attack: geographical analysis of spam in a URL shortener network","authors":"Florian Klien, Markus Strohmaier","doi":"10.1145/2309996.2310010","DOIUrl":"https://doi.org/10.1145/2309996.2310010","url":null,"abstract":"URL shortener services today have come to play an important role in our social media landscape. They direct user attention and disseminate information in online social media such as Twitter or Facebook. Shortener services typically provide short URLs in exchange for long URLs. These short URLs can then be shared and diffused by users via online social media, e-mail or other forms of electronic communication. When another user clicks on the shortened URL, she will be redirected to the underlying long URL. Shortened URLs can serve many legitimate purposes, such as click tracking, but can also serve illicit behavior such as fraud, deceit and spam. Although usage of URL shortener services today is ubiquituous, our research community knows little about how exactly these services are used and what purposes they serve. In this paper, we study usage logs of a URL shortener service that has been operated by our group for more than a year. We expose the extent of spamming taking place in our logs, and provide first insights into the planetary-scale of this problem. Our results are relevant for researchers and engineers interested in understanding the emerging phenomenon and dangers of spamming via URL shortener services.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"4 1","pages":"83-88"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78228556","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}
Computational journalism allows journalists to collect large collections of information chunks from separate sources. The analysis of these collections can reveal hidden relationships between of relationships, but due to their size, diversity, and varying nuances it is necessary to use both computational and human analysis. Breadcrumbs PDL is an adaptive spatial hypermedia system that brings together human cognition and machine computation in order to analyze a collection of user-generated news clips. The project demonstrates the effectiveness of spatial hypermedia in the domain of computational journalism.
{"title":"Adaptive spatial hypermedia in computational journalism","authors":"Luis Francisco-Revilla, Á. Figueira","doi":"10.1145/2309996.2310050","DOIUrl":"https://doi.org/10.1145/2309996.2310050","url":null,"abstract":"Computational journalism allows journalists to collect large collections of information chunks from separate sources. The analysis of these collections can reveal hidden relationships between of relationships, but due to their size, diversity, and varying nuances it is necessary to use both computational and human analysis. Breadcrumbs PDL is an adaptive spatial hypermedia system that brings together human cognition and machine computation in order to analyze a collection of user-generated news clips. The project demonstrates the effectiveness of spatial hypermedia in the domain of computational journalism.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"34 1","pages":"313-314"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85335185","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}
In a curated exhibition of a museum or art gallery, a selection of heritage objects and associated information is presented to a visitor for the purpose of telling a story about them. The same underlying story can be presented in a number of different ways. This paper describes techniques for creating multiple alternative narrative structures from a single underlying story, by selecting different organising principles for the events and plot structures of the story. These authorial decisions can produce different dramatic effects. Storyspace is a web interface to an ontology for describing curatorial narratives. We describe how the narrative component of the Storyspace software can produce multiple narratives from the underlying stories and plots of curated exhibitions. Based on the curator's choice, the narrative module suggests a coherent ordering for the events of a story and its associated heritage objects. Narratives constructed through Storyspace can be tailored to suit different audiences and can be presented in different forms, such as physical exhibitions, museum tours, leaflets and catalogues, or as online experiences.
{"title":"Storyspace: a story-driven approach for creating museum narratives","authors":"A. Wolff, P. Mulholland, T. Collins","doi":"10.1145/2309996.2310012","DOIUrl":"https://doi.org/10.1145/2309996.2310012","url":null,"abstract":"In a curated exhibition of a museum or art gallery, a selection of heritage objects and associated information is presented to a visitor for the purpose of telling a story about them. The same underlying story can be presented in a number of different ways. This paper describes techniques for creating multiple alternative narrative structures from a single underlying story, by selecting different organising principles for the events and plot structures of the story. These authorial decisions can produce different dramatic effects. Storyspace is a web interface to an ontology for describing curatorial narratives. We describe how the narrative component of the Storyspace software can produce multiple narratives from the underlying stories and plots of curated exhibitions. Based on the curator's choice, the narrative module suggests a coherent ordering for the events of a story and its associated heritage objects. Narratives constructed through Storyspace can be tailored to suit different audiences and can be presented in different forms, such as physical exhibitions, museum tours, leaflets and catalogues, or as online experiences.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"13 1","pages":"89-98"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90460495","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}
The explosion of the real-time web has spurred a growing need for new methods to organize, monitor, and distill relevant information from these large-scale social streams. One especially encouraging development is the self-curation of the real-time web via user-driven linking, in which users annotate their own status updates with lightweight semantic annotations -- or hashtags. Unfortunately, there is evidence that hashtag growth is not keeping pace with the growth of the overall real-time web. In a random sample of 3 million tweets, we find that only 10.2% contain at least one hashtag. Hence, in this paper we explore the possibility of predicting hashtags for un-annotated status updates. Toward this end, we propose and evaluate a graph-based prediction framework. Three of the unique features of the approach are: (i) a path aggregation technique for scoring the closeness of terms and hashtags in the graph; (ii) pivot term selection, for identifying high value terms in status updates; and (iii) a dynamic sliding window for recommending hashtags reflecting the current status of the real-time web. Experimentally we find encouraging results in comparison with Bayesian and data mining-based approaches.
{"title":"Predicting semantic annotations on the real-time web","authors":"Elham Khabiri, James Caverlee, K. Kamath","doi":"10.1145/2309996.2310034","DOIUrl":"https://doi.org/10.1145/2309996.2310034","url":null,"abstract":"The explosion of the real-time web has spurred a growing need for new methods to organize, monitor, and distill relevant information from these large-scale social streams. One especially encouraging development is the self-curation of the real-time web via user-driven linking, in which users annotate their own status updates with lightweight semantic annotations -- or hashtags. Unfortunately, there is evidence that hashtag growth is not keeping pace with the growth of the overall real-time web. In a random sample of 3 million tweets, we find that only 10.2% contain at least one hashtag. Hence, in this paper we explore the possibility of predicting hashtags for un-annotated status updates. Toward this end, we propose and evaluate a graph-based prediction framework. Three of the unique features of the approach are: (i) a path aggregation technique for scoring the closeness of terms and hashtags in the graph; (ii) pivot term selection, for identifying high value terms in status updates; and (iii) a dynamic sliding window for recommending hashtags reflecting the current status of the real-time web. Experimentally we find encouraging results in comparison with Bayesian and data mining-based approaches.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"37 1","pages":"219-228"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88651503","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}
Evandro Cunha, Gabriel Magno, Virgílio A. F. Almeida, Marcos André Gonçalves, Fabrício Benevenuto
Gender plays a key role in the process of language variation. Men and women use language in different ways, according to the expected behavior patterns associated with their status in the communities. In this paper, we present a first description of gender distinctions in the usage of Twitter hashtags. After analyzing data collected from more than 650,000 tagged tweets concerning three different subjects, we concluded that gender can be considered a social factor that influences the user's choice of particular hashtags about a given topic. This study aims to increase knowledge about human behavior in free tagging environments and may be useful to the development of tag recommendation systems based on users' collective preferences.
{"title":"A gender based study of tagging behavior in twitter","authors":"Evandro Cunha, Gabriel Magno, Virgílio A. F. Almeida, Marcos André Gonçalves, Fabrício Benevenuto","doi":"10.1145/2309996.2310055","DOIUrl":"https://doi.org/10.1145/2309996.2310055","url":null,"abstract":"Gender plays a key role in the process of language variation. Men and women use language in different ways, according to the expected behavior patterns associated with their status in the communities. In this paper, we present a first description of gender distinctions in the usage of Twitter hashtags. After analyzing data collected from more than 650,000 tagged tweets concerning three different subjects, we concluded that gender can be considered a social factor that influences the user's choice of particular hashtags about a given topic. This study aims to increase knowledge about human behavior in free tagging environments and may be useful to the development of tag recommendation systems based on users' collective preferences.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"15 1","pages":"323-324"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87595271","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}
F. Aisopos, G. Papadakis, K. Tserpes, T. Varvarigou
Microblog content poses serious challenges to the applicability of traditional sentiment analysis and classification methods, due to its inherent characteristics. To tackle them, we introduce a method that relies on two orthogonal, but complementary sources of evidence: content-based features captured by n-gram graphs and context-based ones captured by polarity ratio. Both are language-neutral and noise-tolerant, guaranteeing high effectiveness and robustness in the settings we are considering. To ensure our approach can be integrated into practical applications with large volumes of data, we also aim at enhancing its time efficiency: we propose alternative sets of features with low extraction cost, explore dimensionality reduction and discretization techniques and experiment with multiple classification algorithms. We then evaluate our methods over a large, real-world data set extracted from Twitter, with the outcomes indicating significant improvements over the traditional techniques.
{"title":"Content vs. context for sentiment analysis: a comparative analysis over microblogs","authors":"F. Aisopos, G. Papadakis, K. Tserpes, T. Varvarigou","doi":"10.1145/2309996.2310028","DOIUrl":"https://doi.org/10.1145/2309996.2310028","url":null,"abstract":"Microblog content poses serious challenges to the applicability of traditional sentiment analysis and classification methods, due to its inherent characteristics. To tackle them, we introduce a method that relies on two orthogonal, but complementary sources of evidence: content-based features captured by n-gram graphs and context-based ones captured by polarity ratio. Both are language-neutral and noise-tolerant, guaranteeing high effectiveness and robustness in the settings we are considering. To ensure our approach can be integrated into practical applications with large volumes of data, we also aim at enhancing its time efficiency: we propose alternative sets of features with low extraction cost, explore dimensionality reduction and discretization techniques and experiment with multiple classification algorithms. We then evaluate our methods over a large, real-world data set extracted from Twitter, with the outcomes indicating significant improvements over the traditional techniques.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"103 1","pages":"187-196"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80426040","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}
Rereading often involves reading the same thing again to see something new. This paradox becomes more pronounced in an interactive story, where a reader's choices can literally change what the reader sees in each reading. There has been some discussion of rereading in both non-interactive and interactive stories. There has not, however, been any detailed study of what readers think they are doing as they reread hypertext fiction that changes dynamically as the result of reader choice. An understanding of this would help authors/designers of hypertext fiction create better hypertext that is explicitly intended to encourage rereading. To explore this issue, we conducted semi-structured interviews with participants who repeatedly read a complex hypertext fiction. Participants had trouble describing what they were doing as "rereading", and were looking for either the text, or their understanding of the story, to remain constant between readings. This difficulty highlights the paradoxical nature of rereading in interactive stories, and suggests the need for further research into this phenomenon.
{"title":"The paradox of rereading in hypertext fiction","authors":"A. Mitchell, K. McGee","doi":"10.1145/2309996.2310014","DOIUrl":"https://doi.org/10.1145/2309996.2310014","url":null,"abstract":"Rereading often involves reading the same thing again to see something new. This paradox becomes more pronounced in an interactive story, where a reader's choices can literally change what the reader sees in each reading. There has been some discussion of rereading in both non-interactive and interactive stories. There has not, however, been any detailed study of what readers think they are doing as they reread hypertext fiction that changes dynamically as the result of reader choice. An understanding of this would help authors/designers of hypertext fiction create better hypertext that is explicitly intended to encourage rereading.\u0000 To explore this issue, we conducted semi-structured interviews with participants who repeatedly read a complex hypertext fiction. Participants had trouble describing what they were doing as \"rereading\", and were looking for either the text, or their understanding of the story, to remain constant between readings. This difficulty highlights the paradoxical nature of rereading in interactive stories, and suggests the need for further research into this phenomenon.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"24 1","pages":"103-112"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82967158","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}
Representing and computing pragmatics for linked data requires the usage of various models, including ontology patterns and navigation models, as well as new programming language constructs.
表示和计算关联数据的语用学需要使用各种模型，包括本体模式和导航模型，以及新的编程语言结构。
{"title":"How to do things with triples","authors":"Steffen Staab","doi":"10.1145/2309996.2309998","DOIUrl":"https://doi.org/10.1145/2309996.2309998","url":null,"abstract":"Representing and computing pragmatics for linked data requires the usage of various models, including ontology patterns and navigation models, as well as new programming language constructs.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"17 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82517953","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}
Jérôme Kunegis, Sergej Sizov, F. Schwagereit, D. Fay
Diversity is an important characterization aspect for online social networks that usually denotes the homogeneity of a network's content and structure. This paper addresses the fundamental question of diversity evolution in large-scale online communities over time. In doing so, we study different established notions of network diversity, based on paths in the network, degree distributions, eigenvalues, cycle distributions, and control models. This leads to five appropriate characteristic network statistics that capture corresponding aspects of network diversity: effective diameter, Gini coefficient, fractional network rank, weighted spectral distribution, and number of driver nodes of a network. Consequently, we present and discuss comprehensive experiments with a broad range of directed, undirected, and bipartite networks from several different network categories -- including hyperlink, interaction, and social networks. An important general observation is that network diversity shrinks over time. From the conceptual perspective, our work generalizes previous work on shrinking network diameters, putting it in the context of network diversity. We explain our observations by means of established network models and introduce the novel notion of eigenvalue centrality preferential attachment.
{"title":"Diversity dynamics in online networks","authors":"Jérôme Kunegis, Sergej Sizov, F. Schwagereit, D. Fay","doi":"10.1145/2309996.2310039","DOIUrl":"https://doi.org/10.1145/2309996.2310039","url":null,"abstract":"Diversity is an important characterization aspect for online social networks that usually denotes the homogeneity of a network's content and structure. This paper addresses the fundamental question of diversity evolution in large-scale online communities over time. In doing so, we study different established notions of network diversity, based on paths in the network, degree distributions, eigenvalues, cycle distributions, and control models. This leads to five appropriate characteristic network statistics that capture corresponding aspects of network diversity: effective diameter, Gini coefficient, fractional network rank, weighted spectral distribution, and number of driver nodes of a network. Consequently, we present and discuss comprehensive experiments with a broad range of directed, undirected, and bipartite networks from several different network categories -- including hyperlink, interaction, and social networks. An important general observation is that network diversity shrinks over time. From the conceptual perspective, our work generalizes previous work on shrinking network diameters, putting it in the context of network diversity. We explain our observations by means of established network models and introduce the novel notion of eigenvalue centrality preferential attachment.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"29 1","pages":"255-264"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80303748","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}
In most social networks, measuring similarity between users is crucial for providing new functionalities, understanding the dynamics of such networks, and growing them (e.g., people you may know recommendations depend on similarity, as does link prediction). In this paper, we study a large sample of Flickr user actions and compare tags across different explicit and implicit network relations. In particular, we compare tag similarities in explicit networks (based on contact, friend, and family links), and implicit networks (created by actions such as comments and selecting favorite photos). We perform an in-depth analysis of these five types of links specifically focusing on tagging, and compare different tag similarity metrics. Our motivation is that understanding the differences in such networks, as well as how different similarity metrics perform, can be useful in similarity-based recommendation applications (e.g., collaborative filtering), and in traditional social network analysis problems (e.g., link prediction). We specifically show that different types of relationships require different similarity metrics. Our findings could lead to the construction of better user models, among others.
{"title":"Understanding and leveraging tag-based relations in on-line social networks","authors":"M. Lipczak, Börkur Sigurbjörnsson, A. Jaimes","doi":"10.1145/2309996.2310035","DOIUrl":"https://doi.org/10.1145/2309996.2310035","url":null,"abstract":"In most social networks, measuring similarity between users is crucial for providing new functionalities, understanding the dynamics of such networks, and growing them (e.g., people you may know recommendations depend on similarity, as does link prediction). In this paper, we study a large sample of Flickr user actions and compare tags across different explicit and implicit network relations. In particular, we compare tag similarities in explicit networks (based on contact, friend, and family links), and implicit networks (created by actions such as comments and selecting favorite photos). We perform an in-depth analysis of these five types of links specifically focusing on tagging, and compare different tag similarity metrics. Our motivation is that understanding the differences in such networks, as well as how different similarity metrics perform, can be useful in similarity-based recommendation applications (e.g., collaborative filtering), and in traditional social network analysis problems (e.g., link prediction). We specifically show that different types of relationships require different similarity metrics. Our findings could lead to the construction of better user models, among others.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"12 1","pages":"229-238"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77263936","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}
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