图 书 馆
社交媒体对象描述性注释的有用用户生成评论的属性、预测和流行率Properties, Prediction, and Prevalence of Useful User-Generated Comments for Descriptive Annotation of Social Media Objects |
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| 课程网址: | https://videolectures.net/videos/icwsm2013_momeni_media_objects |
| 主讲教师: | Elaheh Momeni |
| 开课单位: | 信息不详。欢迎您在右侧留言补充。 |
| 开课时间: | 2014-04-03 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | User-generated comments in online social media have recently been gaining increasing attention as a viable source of general-purpose descriptive annotations for digital objects like photos or videos. Because users have different levels of expertise, however, the quality of their comments can vary from very useful to entirely useless. Our aim is to provide automated support for the curation of useful user-generated comments from public collections of digital objects. After constructing a crowd-sourced gold standard of useful and not useful comments, we use standard machine learning methods to develop a usefulness classifier, exploring the impact of surface-level, syntactic, semantic, and topic-based features in addition to extra-linguistic attributes of the author and his or her social media activity. We then adapt an existing model of prevalence detection that uses the learned classifier to investigate patterns in the commenting culture of two popular social media platforms. We find that the prevalence of useful comments is platform-specific and is further influenced by the entity type of the media object being commented on (person, place, event), its time period (e.g., year of an event), and the degree of polarization among commenters. |
| 关 键 词: | 在线社交媒体; 实体类型; 公共数字 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2025-04-23：yuhongrui |
| 最后编审: | 2025-04-23：yuhongrui |
| 阅读次数: | 1 |