垃圾，闪光，还是黄金：将多维质量分数应用于网络档案收集的社交媒体种子
Garbage, Glitter, or Gold: Assigning Multi-dimensional Quality Scores to Social Media Seeds for Web Archive Collections
摘要：
从民众起义到流行病，网络是科学家和历史学家重建和研究过去事件的重要参考来源。不幸的是，Web受到引用腐烂的困扰，导致重要的Web资源消失。Web存档集合通过保存记录重要故事/事件的Web资源，在它们消失之前帮助减少引用腐烂的代价。这些集合通常以称为种子的URL开始，由专家手工选择或从社交媒体上刮取。社会化媒体内容的质量差异很大，因此，我们提出了一个框架，分配多维质量分数的社会化媒体种子的故事和事件的Web档案收集。我们利用社交媒体研究的贡献，根据可信度，声誉和影响力将质量归因于社交媒体内容和用户。我们将这些与来自网络档案研究的额外贡献相结合，强调在选择种子时考虑地理和时间限制的重要性。接下来，我们开发了质量代理（QP）框架，该框架为从社交媒体中提取的种子分配了10个主要维度的质量分数：流行度，地理，时间，主题专家，可检索性，相关性，声誉和稀缺性。我们实例化的框架，并表明，种子可以在多个QP类，映射到不同的政策，如优先种子从本地新闻，信誉良好和/或流行的来源，等QP框架是可扩展的和强大的种子排名。我们的研究结果表明，质量代理导致选择的质量种子增加精度（约0.13）时，新颖性是和不优先。这些贡献提供了一个可解释的分数适用于排名和选择质量种子的Web档案收集和其他领域。
英文摘要：
From popular uprisings to pandemics, the Web is an essential source consulted by scientists and historians for reconstructing and studying past events. Unfortunately, the Web is plagued by reference rot which causes important Web resources to disappear. Web archive collections help reduce the costly effects of reference rot by saving Web resources that chronicle important stories/events before they disappear. These collections often begin with URLs called seeds, hand-selected by experts or scraped from social media. The quality of social media content varies widely, therefore, we propose a framework for assigning multi-dimensional quality scores to social media seeds for Web archive collections about stories and events. We leveraged contributions from social media research for attributing quality to social media content and users based on credibility, reputation, and influence. We combined these with additional contributions from the Web archive research that emphasizes the importance of considering geographical and temporal constraints when selecting seeds. Next, we developed the Quality Proxies (QP) framework which assigns seeds extracted from social media a quality score across 10 major dimensions: popularity, geographical, temporal, subject expert, retrievability, relevance, reputation, and scarcity. We instantiated the framework and showed that seeds can be scored across multiple QP classes that map to different policies for ranking seeds such as prioritizing seeds from local news, reputable and/or popular sources, etc. The QP framework is extensible and robust. Our results showed that Quality Proxies resulted in the selection of quality seeds with increased precision (by ~0.13) when novelty is and is not prioritized. These contributions provide an explainable score applicable to rank and select quality seeds for Web archive collections and other domains.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
