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Identity Management and Mental Health Discourse in Social Media. 社会媒体中的身份管理与心理健康话语
Umashanthi Pavalanathan, Munmun De Choudhury

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.

社交媒体越来越多地被用于健康话语。我们研究了身份在支持社会污名化条件的话语中所起的作用。具体来说,我们关注的是reddit上的心理健康社区。我们调查了心理健康话语的特征,通过reddit的特征“一次性”账户表现出来,这些账户被用作匿名代理。为此,我们从心理学文献中提出了情感、认知、社会和语言风格的测量方法。我们观察到,从丢弃的心理健康话语是相当解除抑制,并表现出增加的消极性,认知偏见和自我关注的焦点,并降低自尊。与其他reddit社区相比,在心理健康论坛上,“一次性垃圾”作为一种身份选择的流行程度似乎也要高出六倍。我们讨论了我们的工作在指导心理健康干预方面的意义,以及在设计能够更好地满足弱势群体需求的在线社区方面的意义。最后,我们对社交媒体上的身份表现在行为治疗中的作用进行了思考。
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引用次数: 105
Donor Retention in Online Crowdfunding Communities: A Case Study of DonorsChoose.org. 在线众筹社区的捐赠者留存:以DonorsChoose.org为例
Tim Althoff, Jure Leskovec

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.

像DonorsChoose.org和kickstarter这样的在线众筹平台允许特定项目通过大量人群的定向捐款获得资金。众筹社区成功的关键是招募和持续参与捐助者。在捐赠者流失率超过70%的情况下,在线众筹平台和传统的线下非营利组织面临的一个重大挑战是捐赠者的保留问题。我们在DonorsChoose.org(一个教育项目众筹平台)上对数百万捐赠者和捐款进行了大规模研究。研究一个在线众筹平台,可以前所未有地详细了解人们如何指导他们的捐款。我们探索了影响捐赠者保留的各种因素,这使我们能够识别不同的捐赠者群体,并量化他们对后续捐赠的回报倾向。我们发现,如果捐赠者与接受者有积极的互动,他们更有可能回报。我们还表明,这包括适当和及时地承认他们的支持,以及详细地沟通他们的影响。最后,我们讨论了我们的研究结果如何为提高众筹社区和非营利组织的捐助者保留率提供信息。
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引用次数: 98
Don't Like RDF Reification? Making Statements about Statements Using Singleton Property. 不喜欢RDF具体化?关于使用Singleton属性的语句的声明。
Vinh Nguyen, Olivier Bodenreider, Amit Sheth

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 Singleton Property 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.

关于RDF语句或元三元组的语句提供了关于单个三元组的附加信息,例如源、发生的时间或地点,或确定性。将这样的元三元组集成到语义知识库中,将使查询和推理机制能够了解三元组的来源、时间、位置或确定性。然而,三元组元知识的有效RDF表示仍然具有挑战性。现有的标准具体化方法允许使用RDF分两个步骤表示RDF三元组的元知识。第一步是用一个Statement实例表示这个三元组,该实例用三个不同的三元组分别表示主语、谓语和宾语。第二步是创建关于该实例的断言,就好像它是一个语句一样。虽然具体化是简单和直观的,但是这种方法没有形式化的语义,并且在实践中并不常用,如RDF Primer中所描述的那样。在本文中,我们提出了一种称为单例属性的新方法来表示关于语句的语句,并为其提供了形式化语义。我们解释了这种单例属性方法如何很好地适应RDF的现有语法和形式语义,以及SPARQL查询语言的语法。我们还以两个语义Web知识库YAGO2和BKR为例,演示了在元知识的表示和查询中使用单例属性。我们在BKR上的实验表明,与现有方法相比,单例属性方法在三元组的数量、查询长度和查询执行时间方面提供了不错的性能。这种方法也简单直观,可以很容易地用于表示和查询其他知识库中关于语句的语句。
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引用次数: 0
Optimizing the Most Specific Concept Method for Efficient Instance Checking. 优化最具体的概念方法以实现有效的实例检查。
Jia Xu, Patrick Shironoshita, Ubbo Visser, Nigel John, Mansur Kabuka

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 SHI, 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.

实例检查被认为是从描述逻辑(DL)本体中检索数据的中心工具。本文提出了一种改进的最具体概念(MSC)方法,将实例检验转化为包含问题。这种修改后的方法可以生成足够具体的小概念,以回答给定的查询,并允许推理仅探索ABox数据的子集以实现效率。实验结果表明,本文提出的方法在减小概念大小和提高推理效率方面是有效的。
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引用次数: 0
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Proceedings of the ... International World-Wide Web Conference. International WWW Conference
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