In this study, Turkish texts belonging to different categories were classified by using
word2vec word vectors. Firstly, vectors of the words in all the texts were extracted then, each …

This paper presents an ongoing project aimed at creation of corpora for minority Uralic
languages that contain texts posted on social media. Corpora for Udmurt and Erzya are fully …

Distributional language models have consistently been demonstrated to capture semantic
properties of words. However, research into the methods for evaluating the accuracy of the …

This paper presents a hybrid algorithm that takes advantage of polarity lexicons along with
state-of-the-art word embeddings with weighted average of reviews and headlines for …

Neural network-based word embeddings–outperforming traditional approaches in the
various Natural Language Processing tasks–have gained a lot of interest recently. Despite it …

Social media use has risen in the Finnish population during the 2010s and is a platform for
discussing products, companies, public figures, and many other topics. Analysing social …

In the digital age, many government agencies need to gather, analyze and make informed
decisions based on constant streams of new digital data. To this aid, developments in the …

In this paper, a document classification system is enhanced through the construction of a text
augmentation technique by testing various Part-of-Speech filters and word vector weighting …

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