TY - GEN
T1 - Analysis of Google Play Store's Sentiment Review on Indonesia's P2P Fintech Platform
AU - Amrie, Syahrul
AU - Kurniawan, Sandy
AU - Windiatmaja, Jauzak Hussaini
AU - Ruldeviyani, Yova
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Nowadays there are so many mobile phone-based investment applications, ranging from mutual funds, stocks, and P2P lending. While these investment applications are gaining huge attraction among the general masses, sometimes selecting the right platform still becomes a hot issue. This research aimed to analyze the sentiment on P2P lending applications and to determine the user's response due to the increase in the number of funds distribution during the COVID-19 pandemic. By doing so, this research could give some insight into the new and existing user. Data was obtained through assessment reviews on the Play store platform for the P2P A, P2P B, and P2P C applications. Assessment reviews were classified by using a data mining approach, TF-IDF feature extraction, and Naïve-Bayes classification method. This research showed that P2P A got 77% positive sentiment and 23% negative sentiment, P2P B got 36% positive sentiment and 64% negative sentiment, and P2P C got 68% positive sentiment and 32% negative sentiment. From the results of the study, it was found that P2P A got better results than both P2P B and P2P C. those were 77% positive sentiment with 23% negative sentiment in finance topic, 56% positive sentiment with 44 % negative sentiment in account verification topic, 79% positive sentiment with 21% negative sentiment in apps review, and 99% positive sentiment with 1% negative sentiment in referral topic.
AB - Nowadays there are so many mobile phone-based investment applications, ranging from mutual funds, stocks, and P2P lending. While these investment applications are gaining huge attraction among the general masses, sometimes selecting the right platform still becomes a hot issue. This research aimed to analyze the sentiment on P2P lending applications and to determine the user's response due to the increase in the number of funds distribution during the COVID-19 pandemic. By doing so, this research could give some insight into the new and existing user. Data was obtained through assessment reviews on the Play store platform for the P2P A, P2P B, and P2P C applications. Assessment reviews were classified by using a data mining approach, TF-IDF feature extraction, and Naïve-Bayes classification method. This research showed that P2P A got 77% positive sentiment and 23% negative sentiment, P2P B got 36% positive sentiment and 64% negative sentiment, and P2P C got 68% positive sentiment and 32% negative sentiment. From the results of the study, it was found that P2P A got better results than both P2P B and P2P C. those were 77% positive sentiment with 23% negative sentiment in finance topic, 56% positive sentiment with 44 % negative sentiment in account verification topic, 79% positive sentiment with 21% negative sentiment in apps review, and 99% positive sentiment with 1% negative sentiment in referral topic.
KW - Naive Bayes Classifier
KW - P2P lending
KW - Sentiment Analysis
KW - TF-IDF
UR - http://www.scopus.com/inward/record.url?scp=85129435148&partnerID=8YFLogxK
U2 - 10.1109/DELCON54057.2022.9753108
DO - 10.1109/DELCON54057.2022.9753108
M3 - Conference contribution
AN - SCOPUS:85129435148
T3 - 2022 IEEE Delhi Section Conference, DELCON 2022
BT - 2022 IEEE Delhi Section Conference, DELCON 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Delhi Section Conference, DELCON 2022
Y2 - 11 February 2022 through 13 February 2022
ER -