{"id":726181,"date":"2021-02-12T08:34:18","date_gmt":"2021-02-12T16:34:18","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=726181"},"modified":"2025-08-26T12:34:56","modified_gmt":"2025-08-26T19:34:56","slug":"i-cant-reply-with-that-characterizing-problematic-email-reply-suggestions","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/i-cant-reply-with-that-characterizing-problematic-email-reply-suggestions\/","title":{"rendered":"&#8220;I Can\u2019t Reply with That&#8221;: Characterizing Problematic Email Reply Suggestions"},"content":{"rendered":"<p>In email interfaces, providing users with reply suggestions may simplify or accelerate correspondence.\u00a0 While the &#8220;success'&#8221; of such systems is typically quantified using the number of suggestions selected by users, this ignores the impact of social context, which can change how suggestions are perceived.\u00a0 To address this, we developed a mixed-methods framework involving qualitative interviews and crowdsourced experiments to characterize problematic email reply suggestions.\u00a0 Our interviews revealed issues with over-positive, dissonant, cultural, and gender-assuming replies, as well as contextual politeness.\u00a0 In our experiments, crowdworkers assessed email scenarios that we generated and systematically controlled, showing that contextual factors like social ties and the presence of salutations impacts users&#8217; perceptions of email correspondence.\u00a0 These assessments created a novel dataset of human-authored corrections for problematic email replies. Our study highlights the social complexity of providing suggestions for email correspondence, raising issues that may apply to all social messaging systems.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In email interfaces, providing users with reply suggestions may simplify or accelerate correspondence.\u00a0 While the &#8220;success&#8217;&#8221; of such systems is typically quantified using the number of suggestions selected by users, this ignores the impact of social context, which can change how suggestions are perceived.\u00a0 To address this, we developed a mixed-methods framework involving qualitative interviews 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