A Logical Approach to Sentiment Analysis |
Niklas Christoffer Petersen
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| Abstract | This thesis presents a formal logical approach for entity level sentiment analysis which utilizes machine learning techniques for efficient syntactical tagging, and performs a deep structural analysis of the syntactical properties of texts in order to yield precise results.
The method should be seen as an alternative to pure machine learning methods for sentiment analysis, which are argued to have high difficulties in capturing long distance dependencies, and be dependent on significant amount of domain specific training data.
To demonstrate the method a proof of concept implementation is presented, and used for testing the method on real data sets. The results shows that the method yields high correctness, but further investment are needed in order to improve its robustness. |
| Type | Master's thesis [Academic thesis] |
| Year | 2012 |
| Publisher | Technical University of Denmark, DTU Informatics, E-mail: reception@imm.dtu.dk |
| Address | Asmussens Alle, Building 305, DK-2800 Kgs. Lyngby, Denmark |
| Series | IMM-M.Sc.-2012-126 |
| Note | |
| Electronic version(s) | [pdf] |
| Publication link | http://www.imm.dtu.dk/English.aspx |
| BibTeX data | [bibtex] |
| IMM Group(s) | Computer Science & Engineering |