Topic modelling of Finnish Internet discussion forums as a tool for trend identification and marketing applications

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Koski, Mikko Särkiö, Ilkka 2019-03-17T16:04:48Z 2019-03-17T16:04:48Z 2019-03-12
dc.description.abstract The increasing availability of public discussion text data on the Internet motivates to study methods to identify current themes and trends. Being able to extract and summarize relevant information from public data in real time gives rise to competitive advantage and applications in the marketing actions of a company. This thesis presents a method of topic modelling and trend identification to extract information from Finnish Internet discussion forums. The development of text analytics, and especially topic modelling techniques, is reviewed and suitable methods are identified from the literature. The Latent Dirichlet Allocation topic model and the Dynamic Topic Model are applied in finding underlying topics from the Internet discussion forum data. The discussion data collection with web scarping and text data preprocessing methods are presented. Trends are identified with a method derived from outlier detection. Real world events, such as the news about Finnish army vegetarian meal day and the Helsinki summit of presidents Trump and Putin, were identified in an unsupervised manner. Applications for marketing are considered, e.g. automatic search engine advert keyword generation and website content recommendation. Future prospects for further improving the developed topical trend identification method are proposed. This includes the use of more complex topic models, extensive framework for tuning trend identification parameters and studying the use of more domain specific text data sources such as blogs, social media feeds or customer feedback. en
dc.format.extent 78+35
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title Topic modelling of Finnish Internet discussion forums as a tool for trend identification and marketing applications en
dc.type G2 Pro gradu, diplomityö fi Perustieteiden korkeakoulu fi
dc.subject.keyword topic modelling en
dc.subject.keyword social media en
dc.subject.keyword natural language processing en
dc.subject.keyword text analytics en
dc.subject.keyword trend identification en
dc.subject.keyword digital marketing en
dc.identifier.urn URN:NBN:fi:aalto-201903172292
dc.programme.major Systems and Operations Research fi
dc.programme.mcode SCI3055 fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Diplomityö fi
dc.contributor.supervisor Ilmonen, Pauliina
dc.programme Master’s Programme in Mathematics and Operations Research fi
local.aalto.electroniconly yes
local.aalto.openaccess yes

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