论文标题
应用单词嵌入以测量针对巴西记者的信息操作中的价值
Applying Word Embeddings to Measure Valence in Information Operations Targeting Journalists in Brazil
论文作者
论文摘要
信息操作的目标之一是改变特定参与者的整体信息环境。例如,“拖钓运动”试图破坏特定公众人物的信誉,导致其他人不信任他们,并将这些数字吓到沉默。为了实现这些目标,信息操作经常利用“巨魔” - 针对这些数字的口头虐待的恶意在线演员。尤其是在巴西,巴西现任总统的盟友被指控经营“仇恨内阁”,这是一个拖钓的行动,针对那些据称由该政治家和他政权的其他成员腐败的记者。检测有害语音的领先方法,例如Google的观点API,试图识别具有有害内容的特定信息。虽然这种方法有助于识别出向下层,标志或删除的内容,但已知它是脆弱的,可能会错过试图将更多微妙的偏见引入话语中。在这里,我们旨在制定一种可能用于评估目标信息操作如何试图改变特定参与者的总体价或评估的措施。初步结果表明,已知的运动比男性记者更重要,并且这些运动可能会在Twitter总体话语中留下可检测到的痕迹。
Among the goals of information operations are to change the overall information environment vis-á-vis specific actors. For example, "trolling campaigns" seek to undermine the credibility of specific public figures, leading others to distrust them and intimidating these figures into silence. To accomplish these aims, information operations frequently make use of "trolls" -- malicious online actors who target verbal abuse at these figures. In Brazil, in particular, allies of Brazil's current president have been accused of operating a "hate cabinet" -- a trolling operation that targets journalists who have alleged corruption by this politician and other members of his regime. Leading approaches to detecting harmful speech, such as Google's Perspective API, seek to identify specific messages with harmful content. While this approach is helpful in identifying content to downrank, flag, or remove, it is known to be brittle, and may miss attempts to introduce more subtle biases into the discourse. Here, we aim to develop a measure that might be used to assess how targeted information operations seek to change the overall valence, or appraisal, of specific actors. Preliminary results suggest known campaigns target female journalists more so than male journalists, and that these campaigns may leave detectable traces in overall Twitter discourse.