TY - GEN
T1 - SNS Data Based Tweet Similarity Evaluation for QoE Estimation
AU - Kirikae, Takaaki
AU - Zhang, Cheng
AU - Yamori, Kyoko
AU - Tanaka, Yoshiaki
N1 - Publisher Copyright:
© 2020 IEICE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/7
Y1 - 2020/7
N2 - Quality of experience (QoE) cannot be evaluated only by simple quality measurement, since it is related to user's subjective evaluation, the specific application, purpose of use, etc. On the other hand, it is expected that the remarks on social network service (SNS) probably include the user's subjectivity. Estimating QoE from SNS remarks data has been considered in existing research. One problem in existing research is that communication quality related negative expression search is implemented by extracting negative words uniformly from a negative expression dictionary. Then, the meaning of each tweet is difficult to analyze. Therefore, user's subjectivity or QoE, cannot be estimated by extracting only negative words from the user's tweet. In this paper, as the first step of QoE estimation research, similarity of tweets is evaluated. The possibility of QoE estimation from tweets on communication quality has been verified through experiments with 168 tweets from 20 subjects. The experiment results show that it is possible to estimate QoE from tweets.
AB - Quality of experience (QoE) cannot be evaluated only by simple quality measurement, since it is related to user's subjective evaluation, the specific application, purpose of use, etc. On the other hand, it is expected that the remarks on social network service (SNS) probably include the user's subjectivity. Estimating QoE from SNS remarks data has been considered in existing research. One problem in existing research is that communication quality related negative expression search is implemented by extracting negative words uniformly from a negative expression dictionary. Then, the meaning of each tweet is difficult to analyze. Therefore, user's subjectivity or QoE, cannot be estimated by extracting only negative words from the user's tweet. In this paper, as the first step of QoE estimation research, similarity of tweets is evaluated. The possibility of QoE estimation from tweets on communication quality has been verified through experiments with 168 tweets from 20 subjects. The experiment results show that it is possible to estimate QoE from tweets.
KW - Doc2Vec
KW - MeCab
KW - QoE
KW - SNS
KW - Word2Vec
UR - http://www.scopus.com/inward/record.url?scp=85091437225&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091437225&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85091437225
T3 - ITC-CSCC 2020 - 35th International Technical Conference on Circuits/Systems, Computers and Communications
SP - 269
EP - 272
BT - ITC-CSCC 2020 - 35th International Technical Conference on Circuits/Systems, Computers and Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2020
Y2 - 3 July 2020 through 6 July 2020
ER -