Available Data Science M.Sc. Thesis Proposals
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This document discusses 7 problems related to human-generated content and quantitative analysis. The first problem involves knowledge extraction from data, information, and knowledge. The second problem examines analyzing social spaces using data from services like Foursquare and Flickr. The third problem looks at analyzing social aspects of software development using data from GitHub and developer communities. The fourth problem is applying machine learning to computational social science topics like politics, debates, and societal issues. The fifth problem relates to using knowledge bases to help with content understanding tasks. The sixth problem discusses using digital humanities to engage citizens in envisioning future policies and visions. The seventh problem covers developing data models to help with mobility services.
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Available Data Science M.Sc. Thesis Proposals
- 1. Theses on Human-generated Content and Quantitative Analysis Marco Brambilla marco.brambilla@polimi.it marcobrambi
- 3. The Answer to the Great Question... Of Life, the Universe and Everything Data Information Knowledge WisdomContext independence Understanding Understanding relations Understanding patterns Understanding principles
- 4. Overview
- 5. Knowledge Enrichment Setting HF Entity1 HF Entity5 HF Entity2 HF Entity4 HF Entity3 LF Entity1 ?? LF Entity2 LF Entity4 LF Entity3 ?? High Frequency Entities Low Frequency Entities ?? ?? ???? ?? Type1 Type11 Type2 Type111 Instances Types <<instanceof>> <<instanceof>> <<instanceof>> <<instanceof>> <<instanceof>> <<instanceof>> ?? ?? ?? ?? ?? Seed Entity Seed Type Type of interest Legend Expert inputs Enrichment problems Property2 Relations HF - LF entities Relations LF - LF entities Typing of LF entities Extraction of new LF entities Property1 ?? ?? ?? Finding attribute values
- 7. Input (1): Domain Specific Types Types selected by the expert Relevant for the domain
- 8. Input (2): Seeds (emerging entities) Known and selected by the domain expert Belonging to an expert type Thoroughly Described # @ w
- 9. Objectives (1) Discover candidate unknown emerging entities (2) Determine the relevance of the candidate (3) Determine the type of the candidate
- 10. Building Triples (Subject-Predicate-Object) Relation extraction Subject and object extraction Triples composition Beautiful #AngelinaJolie on the cover of @THR wears Amen silk top wear (Verb - Relation) Triples Objects Relations Subjects Beautiful #AngelinaJolie on the cover of @THR wears Amen silk top #AngelinaJ olie (Subj.) Amen silk top (Obj.)
- 11. Problem 2. Social Spaces: Volume, Consumption, Presence, Flows
- 13. Not only space…
- 14. Model of social media and reality sensing
- 15. Model of social media and reality sensing
- 16. Model of social media and reality sensing
- 18. 18 Cities into cities, by language http://urbanscope.polimi.it
- 19. Foursquare • Check-ins explicitly performed in venues all around the world • Data set: Geo-localized Foursquare venues, collected through a query every 50m with radius >50m over: • Milan area: 20km x 17,5km • Some numbers • Total n° of venues: 90K (dirty) • Total n° of valid venues: 43K
- 20. Google Places Only in the UI (scraping) Via API
- 21. Correlation Google Place - Foursquare Dataset # obs Min 1Q Median 3Q Max Grid 230 -06406 0.0744 0.3536 0.5529 0.8796 Place 283 -0.6406 0.0654 0.3569 0.5829 0.8796
- 22. Electricity Consumption data • Electrical hubs + mobile phone calls • Grid-based analysis
- 23. • Which locations do people visit from where? Statistics about nationality
- 24. Event location per cluster of users
- 25. Approach City-scale: mobile telephone and (gross-grain geo-located) social media data Street/square: people counting & profiling IoT sensors Point of Interest: people counting sensor, WiFi log analysis, beacons and (fine grain geo- located) social media Descriptive, predictive, privacy-preserving and, when needed, real-time analysis of a variety of (fused) data sources
- 26. Problem 3. Social Aspects of Sw. Development
- 27. Collaborative activities on sw. development • Development repositories • Github • Developer communities • Interactions and contributions • Networks (social?) Machine learning on network data, Representation learning In collaboration with UOC, Barcelona
- 28. • Roles of developers
- 29. Collaboration networks • Cross-project collaborations • Networking
- 31. Politics, Debates and Other Societal Issues • BREXIT • US Political Observer • Other cases
- 32. US Midterm • Antonio Lopardo
- 33. Brexit • Emre Calisir, now @ MIT Media Lab 33
- 34. Brexit
- 35. Radio Shows & Public Debates • 60 stations real time radio transcripts • Twitter data in some US states • Collaboration with MIT & cortico.ai
- 36. News and News Sharing • Understanding how and when people share pieces of news on social network • Profiling users against possible risks (fake news, superficial behaviour)
- 38. KB and Text • How can I use KBs for improving… • Topic analysis • Other general NLP tasks • Pre-trained models available (language models, …) • https://www.aaai-make.info/
- 39. Problem 6. Digital Humanities for the Future
- 40. Engagement for Future Visions • Mission-oriented policies • Gamification and user engagement for policy directions
- 42. Engage SHARED VISION New way of engaging citizens The evolution of the PE spectrum
- 43. Images are the new esperanto
- 44. Gamification • The process of game-thinking and game mechanics to engage users and solve problems • Turning user experience into a game can produce behavior change
- 45. KB and Text • Possible futures • The KB of science fiction • Asimov, …
- 46. Alexa, Tell me a NEW Story • NN-based approaches for generating new content • Stories for children • Jokes !?
- 48. Data Models for Gita
- 49. Further Problems
- 50. … • ANN for solving differential equations ( with Harvard IACS) • Conditional GANs for generating data for specific contexts (with Harvard IACS)
- 51. THANKS! QUESTIONS? Marco Brambilla @marcobrambi marco.brambilla@polimi.it http://datascience.deib.polimi.it http://home.deib.polimi.it/marcobrambi