Investigating Contextual Cues as Indicators for EMA Delivery

被引：10

作者：

Mishra, Varun ^{[1
]}

Lowens, Byron ^{[2
]}

Lord, Sarah ^{[1
]}

Caine, Kelly ^{[2
]}

Kotz, David ^{[1
]}

机构：

[1] Dartmouth Coll, Hanover, NH 03755 USA

[2] Clemson Univ, Clemson, SC USA

来源：

PROCEEDINGS OF THE 2017 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2017 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (UBICOMP/ISWC '17 ADJUNCT) | 2017年

基金：

美国国家科学基金会;

关键词：

Ecological Momentary Assessment; Notification; Interruptibility; Mobile sensing; Context-aware computing;

D O I：

10.1145/3123024.3124571

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this work, we attempt to determine whether the contextual information of a participant can be used to predict whether the participant will respond to a particular Ecological Momentary Assessment (EMA) trigger. We use a publicly available dataset for our work, and find that by using basic contextual features about the participant's activity, conversation status, audio, and location, we can predict if an EMA triggered at a particular time will be answered with a precision of 0.647, which is significantly higher than a baseline precision of 0.41. Using this knowledge, the researchers conducting field studies can efficiently schedule EMAs and achieve higher response rates.

引用

页码：935 / 940

页数：6

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