Automatic Prediction of News Popularity Based on Text Semantic Space

Student: Lepigina Anastasia

Supervisor: Nikolay Karpov

Faculty: Faculty of Humanities (Nizhny Novgorod)

Educational Programme: Fundamental and Applied Linguistics (Bachelor)

Year of Graduation: 2018

In the current work it is investigated how different news headings representations impact on quality of their popularity predictions. It was found, that reflecting headings into semantic space makes work of predictor better, compared to extracting different features.

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses