Opportunities for Automating Email Processing: A Need-Finding Study
Email management consumes significant effort from senders and recipients. Some of this work might be automatable. We performed a mixed-methods need-finding study to learn: (i) what sort of automatic email handling users want, and (ii) what kinds of information and computation are needed to support t...
| Main Authors: | , , , |
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| Outros Autores: | |
| Formato: | Artigo |
| Idioma: | English |
| Publicado em: |
Association for Computing Machinery (ACM)
2021
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| Acesso em linha: | https://hdl.handle.net/1721.1/129464 |
| _version_ | 1826195325327507456 |
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| author | Park, Soya Zhang, Amy Xian Murray, Luke S. Karger, David R |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Park, Soya Zhang, Amy Xian Murray, Luke S. Karger, David R |
| author_sort | Park, Soya |
| collection | MIT |
| description | Email management consumes significant effort from senders and recipients. Some of this work might be automatable. We performed a mixed-methods need-finding study to learn: (i) what sort of automatic email handling users want, and (ii) what kinds of information and computation are needed to support that automation. Our investigation included a design workshop to identify categories of needs, a survey to better understand those categories, and a classification of existing email automation software to determine which needs have been addressed. Our results highlight the need for: a richer data model for rules, more ways to manage attention, leveraging internal and external email context, complex processing such as response aggregation, and affordances for senders. To further investigate our findings, we developed a platform for authoring small scripts over a user’s inbox. Of the automations found in our studies, half are impossible in popular email clients, motivating new design directions. |
| first_indexed | 2024-09-23T10:11:02Z |
| format | Article |
| id | mit-1721.1/129464 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T10:11:02Z |
| publishDate | 2021 |
| publisher | Association for Computing Machinery (ACM) |
| record_format | dspace |
| spelling | mit-1721.1/1294642022-09-30T19:26:36Z Opportunities for Automating Email Processing: A Need-Finding Study Park, Soya Zhang, Amy Xian Murray, Luke S. Karger, David R Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Email management consumes significant effort from senders and recipients. Some of this work might be automatable. We performed a mixed-methods need-finding study to learn: (i) what sort of automatic email handling users want, and (ii) what kinds of information and computation are needed to support that automation. Our investigation included a design workshop to identify categories of needs, a survey to better understand those categories, and a classification of existing email automation software to determine which needs have been addressed. Our results highlight the need for: a richer data model for rules, more ways to manage attention, leveraging internal and external email context, complex processing such as response aggregation, and affordances for senders. To further investigate our findings, we developed a platform for authoring small scripts over a user’s inbox. Of the automations found in our studies, half are impossible in popular email clients, motivating new design directions. 2021-01-20T15:41:56Z 2021-01-20T15:41:56Z 2019-05 2020-12-23T15:32:36Z Article http://purl.org/eprint/type/ConferencePaper 9781450359702 https://hdl.handle.net/1721.1/129464 Park, Soya et al. "Opportunities for Automating Email Processing: A Need-Finding Study." Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, May 2019, Glasgow, Scotland, Association for Computing Machinery, May 2019. © 2019 Association for Computing Machinery en http://dx.doi.org/10.1145/3290605.3300604 Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Association for Computing Machinery (ACM) MIT web domain |
| spellingShingle | Park, Soya Zhang, Amy Xian Murray, Luke S. Karger, David R Opportunities for Automating Email Processing: A Need-Finding Study |
| title | Opportunities for Automating Email Processing: A Need-Finding Study |
| title_full | Opportunities for Automating Email Processing: A Need-Finding Study |
| title_fullStr | Opportunities for Automating Email Processing: A Need-Finding Study |
| title_full_unstemmed | Opportunities for Automating Email Processing: A Need-Finding Study |
| title_short | Opportunities for Automating Email Processing: A Need-Finding Study |
| title_sort | opportunities for automating email processing a need finding study |
| url | https://hdl.handle.net/1721.1/129464 |
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