RAPID: A Quasi-Experimental Study of Corporate Policy Effects

为了回应公众对社交媒体中辱骂和负面信息的强烈抗议，社交媒体机构正在着手进行一系列政策改革，以澄清现有标准，促进更多的举报和删除辱骂内容。该研究将通过对任何政策变化之前和之后发送的在线消息的情绪分析来研究这些规则变化对负面消息的影响。通过确定规则变化影响中的个人和地理差异的来源，它将揭示塑造对公司规则的反应以及促成网络攻击模式的社会和文化因素。这项研究还将确定组织的做法，帮助，或没有帮助，在限制日常在线互动的负面性。这项研究将使用不同学科的专业知识的融合，以实现其目标。 数据将来自三个来源：1）基于人口统计特征针对个人的在线消息，2）包含常见诽谤的消息，以及3）包含发布位置（地理标记）的消息。 将通过扩展地理可视化和分析技术以及信息检索方法，并通过使用计算方法来计算情绪和评估社交媒体信息的积极性和消极性，来捕获和处理这些信息。 统计分析将显示新的公司规则是否会导致情绪负面水平的显着下降或可能上升。 它们还将显示，在公司规则发生变化后，滥用通信是否变得更加回避和难以识别。

In response to public outcry over abusive and negative messages in social media, social media outlets are embarking on a set of policy changes to clarify existing standards and facilitate more reporting and removal of abusive content. The research will examine the effect of these rule changes on negative messages through sentiment analyses of online messages sent before and after any policy shifts. By identifying sources of individual and geographic variation in the effects of the rule changes, it will shed light on the social and cultural factors that shape responses to corporate rules and that contribute to patterns of cyber aggression. The research also will identify organizational practices that aid, or fail to aid, in limiting the negativity of everyday online interactions.This research will use a convergence of expertise in different disciplines to accomplish its goals. Data will come from three sources: 1) online messages that target individuals on the basis of their demographic characteristics, 2) messages that contain common slurs, and 3) messages that include the location from which they were posted (geo-tagged). These will be captured and processed by extending geographic visualization and analysis techniques and information retrieval methods, and by using computational methods to compute sentiment and to assess the positivity and negativity of social media messages. Statistical analyses will show if new corporate rules result in significant decreases or possibly increases in level of sentiment negativity. They also will show whether abusive communications become more evasive and less identifiable following corporate rule changes.