Data mining to discover trends on social media

数据挖掘以发现社交媒体趋势

• 批准号: 486701-2015
• 负责人: Gopalakrishnan, Sathish
• 金额: $ 1.63万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=585749
• 关键词: Data; mining; discover; trends; social

Content on social media platforms such as YouTube is often user-generated and is now the predominant form of information consumption and sharing. The ability of many millions of users to generate content leads to information glut that requires new methods for searching and filtering content that is available on these platforms. On the other hand, some content becomes extremely popular and have a large audience and a majority of the content receives little attention. The central question that we would like to begin answering through this study can be stated as follows: "What makes certain social media content dramatically popular?" Related to this major question are a few other questions: -- What factors affect the evolution of a social media object with time? -- What is the impact of the social context within which an object is created and made available? The social context includes the author, the author's social neighborhood, and the nature of the content itself. -- Are there specific interventions - including metadata modifications (when possible) - that affect object popularity? By answering these questions, we hope to identify guidelines for selecting objects that are likely to become popular as well as actions that can be taken to improve the popularity of objects. These observations can guide content creators as well as groups such as our partner organization, BBTV, in marketing social media content.

YouTube等社交媒体平台上的内容通常是用户生成的，现在是信息消费和分享的主要形式。数百万用户生成内容的能力导致信息过剩，这就需要新的方法来搜索和过滤这些平台上可用的内容。另一方面，一些内容变得非常受欢迎，拥有大量的受众，而大多数内容很少受到关注。