TY - GEN
T1 - Social media sentiment analysis of consumer purchasing behavior vs consumer confidence index
AU - Shayaa, Shahid
AU - Al-Garadi, Mohammed Ali
AU - Piprani, Arsalan Zahid
AU - Ashraf, Muhammad
AU - Sulaiman, Ainin
N1 - Publisher Copyright:
� 2017 Association for Computing Machinery.
PY - 2017/12/20
Y1 - 2017/12/20
N2 - The immense popularity of big data of social media opens the door for the consumer to express their opinions and views on a wide range of topics like state of economy, disappointment over certain products or services, or express their happiness of making purchases. Sentiments of social media data can be created almost in real time and at less costly rate which is not possible in the case of technique used for consumer confidence index (CCI). CCI is based on structured questionnaire which restrict the respondents into specific domain which is unlike sentiments through social media where people can express their honest and uninfluenced opinions. Furthermore sentiments acquired from social media can reflect consumer confidence representation of large population than traditional methods. With abovementioned advantages of social media data over traditional methods, this study investigates the relationship of social media driven sentiment analysis and CCI. Our results can be inferred as social media can offer huge data that can be integrated to current methods in synergistic way to better predicate consumer confidence index using far larger populations.
AB - The immense popularity of big data of social media opens the door for the consumer to express their opinions and views on a wide range of topics like state of economy, disappointment over certain products or services, or express their happiness of making purchases. Sentiments of social media data can be created almost in real time and at less costly rate which is not possible in the case of technique used for consumer confidence index (CCI). CCI is based on structured questionnaire which restrict the respondents into specific domain which is unlike sentiments through social media where people can express their honest and uninfluenced opinions. Furthermore sentiments acquired from social media can reflect consumer confidence representation of large population than traditional methods. With abovementioned advantages of social media data over traditional methods, this study investigates the relationship of social media driven sentiment analysis and CCI. Our results can be inferred as social media can offer huge data that can be integrated to current methods in synergistic way to better predicate consumer confidence index using far larger populations.
KW - Big data
KW - Consumer confidence index
KW - Sentiment scores
UR - https://www.scopus.com/pages/publications/85046687382
U2 - 10.1145/3175684.3175712
DO - 10.1145/3175684.3175712
M3 - Conference contribution
AN - SCOPUS:85046687382
T3 - ACM International Conference Proceeding Series
SP - 32
EP - 35
BT - BDIOT 2017 - Proceedings of the International Conference on Big Data and Internet of Thing
PB - Association for Computing Machinery
T2 - 2017 International Conference on Big Data and Internet of Thing, BDIOT 2017
Y2 - 20 December 2017 through 22 December 2017
ER -