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verify-tag🇵🇭 Philippine FinTech Apps Google Store Reviews

TabularFinanceRatings and ReviewsBankingE-Commerce Services

3

已售 0
188.55MB

数据标识:D17169751791821673

发布时间:2024/05/29

以下为卖家选择提供的数据验证报告:

数据描述

About Dataset

App Reviews

  1. ph.com.tala- 299783 records
  2. com.paymaya- 177175 records
  3. ph.homecredit.myhomecredit- 74624 records
  4. com.tmart.pesoq- 60441 records
  5. ph.billeasev2.mobile- 41512 records
  6. www.mobile.bdo.com.ph- 37243 records
  7. ph.moneycat- 33887 records
  8. com.fronde.mbanking.android.pckg.bpi- 29393 records
  9. ph.onlineloans.mobile.android- 28248 records
  10. tech.codeblock.okpeso- 28163 records
  11. com.unionbankph.online- 27482 records
  12. com.mocamoca- 26735 records
  13. com.juanhand.fast.cash.peso.loan.app- 23381 records
  14. com.pesoloan- 23296 records
  15. com.tonik.mobile- 19681 records
  16. com.abs.pesobuffet.android- 16125 records
  17. com.landbank.mobilebanking- 15577 records
  18. prima.Loan.peso.cash.lending- 14741 records
  19. com.bpi.ng.app- 13700 records
  20. com.cimbph.app2022- 12361 records
  21. ph.loans.mobile- 10711 records
  22. ph.lhl.pautangpeso- 10305 records
  23. com.luck.duck.quickla- 9816 records
  24. com.palawanpay.ewallet- 8623 records
  25. com.citibank.CitibankPH- 8169 records
  26. u.money.spend- 7411 records
  27. ph.com.bdo.retail- 6686 records
  28. com.loans.lending.onlinelend.mabiliscash- 6156 records
  29. com.securitybank.online- 6146 records
  30. ph.com.metrobank.mcc.mbonline- 5121 records
  31. com.rcbc.mobilebanking- 5004 records
  32. com.wow.pera- 4837 records
  33. com.peramoo- 4544 records
  34. com.valley.loan- 3561 records
  35. com.liang.chan- 2640 records
  36. hb.xinxinxr.vip- 2255 records
  37. ph.com.gotyme- 2245 records
  38. com.plentina.app- 2037 records
  39. ph.seabank.seabank- 1819 records
  40. ph.komo.app- 1692 records
  41. com.iexceed.unoConsumerBanking- 1012 records
  42. ph.uniondigital.superapp- 225 records

Usage

This dataset should paint a good picture on what is the public's perception of the apps over the years. Using this dataset, we can do the following

  1. Extract sentiments and trends
  2. Identify which version of an app had the most positive feedback, the worst.
  3. Use topic modelling to identify the pain points of the application.

(AND MANY MORE!)

Note

Images generated using Bing Image Generator

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🇵🇭 Philippine FinTech Apps Google Store Reviews
3
已售 0
188.55MB
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