Intelligent Methods and Models for Mining Community Knowledge: Enabling enriched Understanding of Urban Development in Helsinki Metropolitan Region with Social Intelligence (DIGILENS-HKI)

Projektin kuvaus (englanniksi):

Social media presents a rich and timely source of community knowledge and information that has enabled applications such as earthquake detection or identifying the location of missing persons during natural disasters, etc. Social media also abundances with potentially very valuable information and knowledge assets for enriching our understanding of topics in the regional development of the greater Helsinki. The latest breakthrough developments in AI, deep learning methods and tools have brought rapid developments in natural language technology and multimedia information processing, empowered automated tools for social media content analysis. This brings new opportunities for better making use of community knowledge in the social media channels. In this project, we will study intelligent methods and models for social media content analysis and sentiment analysis, with applications relevant to important analytical questions in Helsinki metropolitan regional development. More specifically, we will develop, validate and test models and tools for analyzing and extracting information from social media data relevant for supporting and enriching the analysis of green infrastructure and tourism, cycling planning as well as neighborhood identity and reputation in Helsinki region. Our project will contribute to the development of advanced content analysis methods and models, to the exploration of innovative analytical approaches and potential usefulness of social media data.



Text Analytics and NLP Applications, Artificial Intelligence, Urban Study

Vastaavat tutkijat

Shuhua Liu

+358 50 466 5486


Projektin kesto



Helsinki Metropolitan Region Urban Research Program KaTuMetro (Kaupunkitutkimus ja metropolipolitiikka -tutkimus ja yhteistyöohjelma) and Arcada TUF Foundation


Digital Geography Lab, University of Helsinki