DMW Final Projects

Data Mining and Wrangling

DMW Final Projects

Data Mining and Wrangling

On Monday, 30 July 2018, the Asian Institute of Management’s Master of Science in Data Science 2019 students will be presenting their final projects under the Data Mining and Wrangling (DMW) class. I am psyched to see what they have come up with in this class. The DMW lecture is handled by Dr. Christian Alis and Ed David, Jr while I and Christian handle the lab sessions.

To learn more about the MS in Data Science program, visit the MSDS website.

DMW Class List of Final Projects

  1. How similar are Philippine news outlets from each other based on their content published through RSS feeds?
  2. What are the distinguishing features and themes that can differentiate unreliable news sources from reliable news sources?
  3. What are peoples’ interests in a certain area, given the tweets with emojis they posted?
  4. Can posts be ‘generally’ grouped so we can have a means of having a description or ‘synopsis’?
  5. Clustering of Philippine government agencies based on their procurement of goods and services
  6. What are the trends of laws passed in our country, segregated by administration?
  7. What are the major subgroups of boardgames based on category, mechanics, and an aggregation of all board game features scraped from BGG?
  8. To Trade or Not to Trade: Using clustering algorithms, can you tell Spot Gold’s ($XAUUSD) price movement using tweets?
  9. Qualifying media-expressed sentiments (e.g. in news articles, in-depth commentaries, and analyst reports) through text analysis to gain insight or general outlook of the financial market.
  10. Can public tweets sent to @MMDA be clustered?
  11. What are the similarities/differences between artists and genres that can be identified through the evaluation of their published song lyrics?
  12. What are the subtopics of news articles about artificial intelligence in the last 30 days?
  13. What are the themes of tweets with hashtag #SONA2018 and how are Twitter users clustered based on their tweets?
  14. How are countries clustered based on their musical inclination?
  15. What are the different kinds of Facebook Workplace users and specify from which category they belong to based on their posts?
  16. What are the different themes of customer feedback for Globe and Smart users in Twitter?
  17. What are the underlying themes in the collection of Philippine legal cases?
  18. Are there similar topics in the tweets that tag Justin Bieber and the tweets that tag Selena Gomez?
  19. What are the evident themes from the patents of select technology of automotive companies from 2008 to 2018?
  20. Can restaurateurs discover customer segments based how they are clustered by common complaints or compliments?
  21. What are the activities that Filipinos are practicing when it comes to zero waste advocacy answering SDG12 on responsible consumption and production?
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Erika Fille Legara
Aboitiz Chair in Data Science

My research interests include complexity science, network science, artificial intelligence, and computational social science.

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