Jialu Liu, Xiang Ren, Jingbo Shang, Taylor Cassidy, Clare R Voss, Jiawei Han
{"title":"Representing Documents via Latent Keyphrase Inference.","authors":"Jialu Liu, Xiang Ren, Jingbo Shang, Taylor Cassidy, Clare R Voss, Jiawei Han","doi":"10.1145/2872427.2883088","DOIUrl":"https://doi.org/10.1145/2872427.2883088","url":null,"abstract":"<p><p>Many text mining approaches adopt bag-of-words or <i>n</i>-grams models to represent documents. Looking beyond just the words, <i>i.e.</i>, the explicit surface forms, in a document can improve a computer's understanding of text. Being aware of this, researchers have proposed concept-based models that rely on a human-curated knowledge base to incorporate other related concepts in the document representation. But these methods are not desirable when applied to vertical domains (<i>e.g.</i>, literature, enterprise, <i>etc.</i>) due to low coverage of in-domain concepts in the general knowledge base and interference from out-of-domain concepts. In this paper, we propose a data-driven model named <i>Latent Keyphrase Inference</i> (<i>LAKI</i>) that represents documents with a vector of closely related domain keyphrases instead of single words or existing concepts in the knowledge base. We show that given a corpus of in-domain documents, topical content units can be learned for each domain keyphrase, which enables a computer to do smart inference to discover latent document keyphrases, going beyond just explicit mentions. Compared with the state-of-art document representation approaches, LAKI fills the gap between bag-of-words and concept-based models by using domain keyphrases as the basic representation unit. It removes dependency on a knowledge base while providing, with keyphrases, readily interpretable representations. When evaluated against 8 other methods on two text mining tasks over two corpora, LAKI outperformed all.</p>","PeriodicalId":74532,"journal":{"name":"Proceedings of the ... International World-Wide Web Conference. International WWW Conference","volume":"2016 ","pages":"1057-1067"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2872427.2883088","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34757346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identity Management and Mental Health Discourse in Social Media.","authors":"Umashanthi Pavalanathan, Munmun De Choudhury","doi":"10.1145/2740908.2743049","DOIUrl":"https://doi.org/10.1145/2740908.2743049","url":null,"abstract":"<p><p>Social media is increasingly being adopted in health discourse. We examine the role played by identity in supporting discourse on socially stigmatized conditions. Specifically, we focus on mental health communities on reddit. We investigate the characteristics of mental health discourse manifested through reddit's characteristic 'throwaway' accounts, which are used as proxies of anonymity. For the purpose, we propose affective, cognitive, social, and linguistic style measures, drawing from literature in psychology. We observe that mental health discourse from throwaways is considerably disinhibiting and exhibits increased negativity, cognitive bias and self-attentional focus, and lowered self-esteem. Throwaways also seem to be six times more prevalent as an identity choice on mental health forums, compared to other reddit communities. We discuss the implications of our work in guiding mental health interventions, and in the design of online communities that can better cater to the needs of vulnerable populations. We conclude with thoughts on the role of identity manifestation on social media in behavioral therapy.</p>","PeriodicalId":74532,"journal":{"name":"Proceedings of the ... International World-Wide Web Conference. International WWW Conference","volume":"2015 Companion","pages":"315-321"},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2740908.2743049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34700417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Donor Retention in Online Crowdfunding Communities: A Case Study of DonorsChoose.org.","authors":"Tim Althoff, Jure Leskovec","doi":"10.1145/2736277.2741120","DOIUrl":"https://doi.org/10.1145/2736277.2741120","url":null,"abstract":"<p><p>Online crowdfunding platforms like DonorsChoose.org and Kick-starter allow specific projects to get funded by targeted contributions from a large number of people. Critical for the success of crowdfunding communities is recruitment and continued engagement of donors. With donor attrition rates above 70%, a significant challenge for online crowdfunding platforms as well as traditional offline non-profit organizations is the problem of donor retention. We present a large-scale study of millions of donors and donations on DonorsChoose.org, a crowdfunding platform for education projects. Studying an online crowdfunding platform allows for an unprecedented detailed view of how people direct their donations. We explore various factors impacting donor retention which allows us to identify different groups of donors and quantify their propensity to return for subsequent donations. We find that donors are more likely to return if they had a positive interaction with the receiver of the donation. We also show that this includes appropriate and timely recognition of their support as well as detailed communication of their impact. Finally, we discuss how our findings could inform steps to improve donor retention in crowdfunding communities and non-profit organizations.</p>","PeriodicalId":74532,"journal":{"name":"Proceedings of the ... International World-Wide Web Conference. International WWW Conference","volume":"2015 ","pages":"34-44"},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2736277.2741120","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34314338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Don't Like RDF Reification? Making Statements about Statements Using Singleton Property.","authors":"Vinh Nguyen, Olivier Bodenreider, Amit Sheth","doi":"10.1145/2566486.2567973","DOIUrl":"10.1145/2566486.2567973","url":null,"abstract":"<p><p>Statements about RDF statements, or meta triples, provide additional information about individual triples, such as the source, the occurring time or place, or the certainty. Integrating such meta triples into semantic knowledge bases would enable the querying and reasoning mechanisms to be aware of provenance, time, location, or certainty of triples. However, an efficient RDF representation for such meta knowledge of triples remains challenging. The existing standard reification approach allows such meta knowledge of RDF triples to be expressed using RDF by two steps. The first step is representing the triple by a Statement instance which has subject, predicate, and object indicated separately in three different triples. The second step is creating assertions about that instance as if it is a statement. While reification is simple and intuitive, this approach does not have formal semantics and is not commonly used in practice as described in the RDF Primer. In this paper, we propose a novel approach called <i>Singleton Property</i> for representing statements about statements and provide a formal semantics for it. We explain how this singleton property approach fits well with the existing syntax and formal semantics of RDF, and the syntax of SPARQL query language. We also demonstrate the use of singleton property in the representation and querying of meta knowledge in two examples of Semantic Web knowledge bases: YAGO2 and BKR. Our experiments on the BKR show that the singleton property approach gives a decent performance in terms of number of triples, query length and query execution time compared to existing approaches. This approach, which is also simple and intuitive, can be easily adopted for representing and querying statements about statements in other knowledge bases.</p>","PeriodicalId":74532,"journal":{"name":"Proceedings of the ... International World-Wide Web Conference. International WWW Conference","volume":"2014 ","pages":"759-770"},"PeriodicalIF":0.0,"publicationDate":"2014-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4350149/pdf/nihms654707.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32994431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jia Xu, Patrick Shironoshita, Ubbo Visser, Nigel John, Mansur Kabuka
{"title":"Optimizing the Most Specific Concept Method for Efficient Instance Checking.","authors":"Jia Xu, Patrick Shironoshita, Ubbo Visser, Nigel John, Mansur Kabuka","doi":"10.1145/2567948.2577294","DOIUrl":"https://doi.org/10.1145/2567948.2577294","url":null,"abstract":"<p><p>Instance checking is considered a central tool for data retrieval from description logic (DL) ontologies. In this paper, we propose a revised most specific concept (MSC) method for DL <i>SHI</i>, which converts instance checking into subsumption problems. This revised method can generate small concepts that are specific-enough to answer a given query, and allow reasoning to explore only a subset of the ABox data to achieve efficiency. Experiments show effectiveness of our proposed method in terms of concept size reduction and the improvement in reasoning efficiency.</p>","PeriodicalId":74532,"journal":{"name":"Proceedings of the ... International World-Wide Web Conference. International WWW Conference","volume":"2014 ","pages":"405-406"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2567948.2577294","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33193038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}