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Understanding Email Use: Predicting Action on a message Laura A. Dabbish Jianwei Wang CSCI6800 Spring 2005.

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Presentation on theme: "Understanding Email Use: Predicting Action on a message Laura A. Dabbish Jianwei Wang CSCI6800 Spring 2005."— Presentation transcript:

1 Understanding Email Use: Predicting Action on a message Laura A. Dabbish Jianwei Wang CSCI6800 Spring 2005

2 Purposes: How people choose to reply to, file or delete email messages Email related behavior as a function of message and user characteristics. Important for understanding communication technology and development of automated tools to help people manage messages.

3 Major purposes email serves Project management, task delegation and reminders Information exchange, storage and retrieval Scheduling and planning Social communication

4 Key message content types Action requests Status updates Reminders Information requests and responses Schedule requests and responses Social content.

5 Web-based survey Section one: collect information about the work context, focusing on the nature of the respondent’s job o The number of projects the respondent works on o Their number of subordinates o Their feeling of time pressure at work

6 Web-based survey (cont.) Section two: ask questions about the respondent’s general patterns of email use o The number of email messages sent and received o The number of messages in the email inbox o general email habits

7 Web-based survey (cont.) Section three: ask for detailed information about five new non-spam messages in the respondent’s email inbox o Message content type o The importance of the message o Characteristics of the sender o The action taken on the message o What they did with the message

8 Survey measures job complexity message importance sender characteristics message content message actions

9 Participants 124 of 1100 (11%) completed the survey at Carnegie Mellon University 38 (30.7%) professors and scientists 40 (32.2%) other staff members 46 (37%) graduate or undergraduate students Age from 20 to 57 (average 30)

10 Basic Email Statistics

11 Conclusions: Email usage varies base on the job role. Professors/scientists read more messages per day than students and other staff. 50% have 105 messages or less in inbox. 25% have 1050 or more messages in inbox. 2.5% have 10000 messages or more in inbox Small inbox size and high number of folders suggests that people file their messages into folders.

12 Email Habits

13 Message Content Distribution

14 Predicting importance of a message Individual difference Job complexity Sender characteristics Message content type

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16 Actions on a Message

17 Predicting message reply action Individual difference Job complexity Sender characteristics Message content type

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20 Conclusions and Implications for HCI Inform direction of future research in HCI from studies of people’s email behaviors, e.g. the areas of intelligent techniques for email handling and email interface design High percentage messages filed or left in the inbox suggests that technology to aid in the location and viewing of messages is an important area of future research for email.

21 Conclusions and Implications for HCI Features of email messages influence attention to the message. Message importance influences the message reply. A user interface that makes the importance of a message visible is useful to help people find messages.

22 Conclusions and Implications for HCI Messages with social content, like messages from friends and family members are more likely to receive immediate response. Message with social content may deserve different treatment in the interface


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