SoCS: Collaborative Research: Novel Algorithms and Interaction Mechanisms to Enhance Social Production
SoCS: Collaborative Research: Novel Algorithms and Interaction Mechanisms to Enhance Social Production
批准号:
1210863
负责人:
Loren Terveen
金额:
$52.71万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-08-01 至 2016-07-31
中文摘要
数以百万计的人使用社交媒体技术来组织自己,以产生有价值的信息和工件,如维基百科,GNU/Linux和PatientsLikeMe。然而,这些社区存在着重大问题:(1)他们的工作是如此之好,让人们保持现有的关系,并找到与他们相似的人,他们可以促进自我隔离和意见两极分化。(2)知识生产已经民主化,但代价是专家参与的价值降低。(3)它们让人们从遥远的地方接触到新鲜的想法,但很少有网站能融入家乡社区丰富的当地知识。该项目通过创建算法和用户界面来解决这些问题,这些算法和用户界面将个人和社区推向更有效的社会联系和互动模式。智力上的优点包括:(1)确定人们用来建立社交网络的原则,他们考虑的潜在联系人的范围,以及他们遇到潜在联系人的背景。(2)不同的社会网络结构的有效性的经验知识,以解决一系列现实的决策任务。(3)新颖的社会推荐算法,最大限度地提高网络的有效性,并建议互动的机会,作为上下文的沟通和connection.Broader影响:这项研究将在两个领域的社会利益,育儿和骑自行车的背景下进行,使显着更广泛的影响。为人们提供信息,让他们有信心更多地骑自行车,从而增加他们的个人健康,减少空气污染,并提高社区凝聚力。研究表明,拥有更大、更多样化社交网络的父母会做出更好的育儿决定,而且父母还会就具体问题寻求专家的建议。因此,一个帮助人们建立有效的社交网络并提供专家教育者的系统会给父母带来直接的好处。更好的父母也往往更多地参与他们的社区;因此,改善社区健康是一个额外的效果。最后,通过研究小组与家长教育工作者的联系,该项目将明确针对最需要支持和信息的低收入家庭的家长。
英文摘要
Millions of people used social media technologies to organize themselves to produce information and artifacts of value, such as Wikipedia, GNU/Linux, and PatientsLikeMe. However, these communities have significant problems: (1) They work so well to let people maintain existing relationships and find others who are similar to them that they can promote self-segregation and opinion polarization. (2) Knowledge production has been democratized, but at the price of devaluing expert participation. (3) They open people to fresh ideas from far-off places, but few sites incorporate the rich local knowledge of home communities. This project addresses these problems by creating algorithms and user interfaces that nudge individuals and communities into more effective patterns of social connections and interaction. The intellectual merit includes: (1) Identification of principles people use to build their social networks, the range of potential contacts they consider, and the contexts in which they encounter potential contacts. (2) Empirical knowledge of the effectiveness of different social network structures for solving a range of realistic decision-making tasks. (3) Novel social recommendation algorithms that maximize network effectiveness and that recommend interaction opportunities that serve as contexts for communication and connection.Broader impacts: This research will be performed in the context of two domains of societal interest, parenting and bicycling, enabling significant broader impacts. Providing people information that gives them confidence to bicycle more increases their personal health, decreases air pollution, and improves community cohesion. Research shows that parents with larger and more diverse social networks make better parenting decisions, and that parents also seek expert advice for specific issues. Therefore, a system that helps people form effective social networks and that provides access to expert educators offers direct benefits to parents. Better parents also tend to be more involved in their communities; thus, improved community health is a bonus effect. Finally, through the research team's connections with parent educators, the project will explicitly target parents from low-income families, who have the greatest needs for support and information.
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会议论文
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资助金额:$24.97万
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财政年份:2011
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Recommender Systems Conference Doctoral Consortium, 2007 (October 19-20, 2007)
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海外基金