Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio...
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Transcript of Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio...
![Page 1: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/1.jpg)
Emotion Detection in Email Customer Care
Narendra Gupta, Mazin Gilbert, and Giuseppe Di FabbrizioAT&T Labs - Research, Inc.
2010 ACL
![Page 2: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/2.jpg)
Outline
[1.Introduction] [2.Emotion detection in emails]
2.1 Classifier
2.2 Feature extraction [3.Annotation] [4.Experiments and evaluation]
![Page 3: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/3.jpg)
1.Introduction
Emotional emails often contain complaints about unfair treatment due to negligence, incompetence, rigid protocols, unfriendly systems, and unresponsive personnel.
Reduce the churni.e., retaining customers who otherwise would have taken their business elsewhere.
![Page 4: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/4.jpg)
1.Introduction
A negative emotional component articulated by phrases like:you suck, disgusted.
Enumerating factual sentences such as:you overcharged, take my business elsewhere.
![Page 5: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/5.jpg)
Outline
[1.Introduction] [2.Emotion detection in emails]
2.1 Classifier
2.2 Feature extraction [3.Annotation] [4.Experiments and evaluation]
![Page 6: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/6.jpg)
2.Emotion detection in emails
We use supervised machine learning techniques to detect emotional emails.
![Page 7: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/7.jpg)
2.Emotion detection in emails2.1 Classifier
We used Boostexter as text classification.
The output of the final classifier f is:i.e., the sum of confidence of all classifiers
The final classifier f can be mapped onto a confidence value between 0 and 1 by a logistic function;
![Page 8: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/8.jpg)
2.Emotion detection in emails2.1 Classifier
Training model:
![Page 9: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/9.jpg)
2.Emotion detection in emails2.2 Feature extraction
Salient features For our data we have identified the eight features listed below.
![Page 10: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/10.jpg)
2.Emotion detection in emails2.2 Feature extraction
![Page 11: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/11.jpg)
2.Emotion detection in emails2.2 Feature extraction
![Page 12: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/12.jpg)
2.Emotion detection in emails2.2 Feature extraction
In the labeling guide for critical emails labelers were instructed to look forsalient features in the email and keep a list of encountered phrases.
We further enriched these lists by: a) using general knowledge of English, we added variations to existing
phrases. b) searching a large body of email text (different from testing) for different
phrases in which key words from known phrases participated.
For example from the known phrase lied to we used the word lied and found a phrase blatantly lied.
![Page 13: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/13.jpg)
Outline
[1.Introduction] [2.Emotion detection in emails]
2.1 Classifier
2.2 Feature extraction [3.Annotation] [4.Experiments and evaluation]
![Page 14: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/14.jpg)
3.Annotation
1) Two different labelers.
2) Kappa : 0.814.
![Page 15: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/15.jpg)
3.Annotation
![Page 16: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/16.jpg)
Outline
[1.Introduction] [2.Emotion detection in emails]
2.1 Classifier
2.2 Feature extraction [3.Annotation] [4.Experiments and evaluation]
![Page 17: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/17.jpg)
4.Experiments and evaluation
We used cross validation (leave-one-out) technique on the test set.
![Page 18: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/18.jpg)
4.Experiments and evaluation
![Page 19: Emotion Detection in Email Customer Care Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio AT&T Labs - Research, Inc. 2010 ACL.](https://reader036.fdocuments.in/reader036/viewer/2022062322/5697bfc21a28abf838ca4b7e/html5/thumbnails/19.jpg)
4.Experiments and evaluation