Zekeriya Anıl Güven

Ege University · Department of Computer Engineering

Understanding the emotions of sharing in social media plays a key role in learning people's thoughts. Knowing the emotion of human being with developing technology provides benefit in various fields. For example, media, marketing and advertising areas allow people to reflect on their use and idea-specific content. In this article, Latent Dirichlet...

Recently, the analysis of textual data has gained importance due to the increase in comments made on web platforms and the need for ready-made answering systems. Therefore, there are many studies in the fields of natural language processing such as text summarization and question answering. In this paper, the accuracy of the BERT language model is...

Nowadays, shopping is done more comfortably and without time constraints with the throwing of e-commerce platforms. These platforms allow consumers to examine reviews before purchasing products. Thus, consumers can decide whether to buy a product with positive or negative comments about the products. In this paper, Turkish sentiment analysis was ca...

Users can freely express their opinions about many events on social media platforms. It may be necessary to analyze the data in order to get the opinion of society about these events. Therefore, sentiment analysis studies are gaining importance today. Many different methods and models are used for sentiment analysis. While language models such as t...

In recent years, deep learning models have been used in the implementation of question answering systems. In this study, the performance of the question answering system was evaluated from the perspective of natural language processing using SQuAD, which was developed to measure the performance of deep learning language models. In line with the eva...

Nowadays, data analysis has become a problem as the amount of data is constantly increasing. In order to overcome this problem in textual data, many models and methods are used in natural language processing. The topic modeling field is one of these methods. Topic modeling allows determining the semantic structure of a text document. Latent Dirichl...

With the development of technology, the use of social media has become quite common. Analyzing comments on social media in areas such as media and advertising plays an important role today. For this reason, new and traditional natural language processing methods are used to detect the emotion of these shares. In this paper, the Latent Dirichlet All...

The development of technology has enabled the use of new ways and methods to determine the emotion of sharing on social media. For areas such as media and advertising, social media plays an important role today. In this study, Latent Dirichlet Allocation (LDA) and Non-Negative Matrix Factorization (NMF) methods in topic modeling were used to determ...

Understanding the reason behind the emotions placed in the social media plays a key role to learn mood characterization of any written texts that are not seen before. Knowing how to classify the mood characterization leads this technology to be useful in a variety of fields. The Latent Dirichlet Allocation (LDA), a topic modeling algorithm, was use...

Today, with the increase of Internet-based documents, we are presented with many data that need to be processed and evaluated. Media, news and advertising are some of the areas where these data are evaluated. For the news, the classification of people in the media sector is an important problem in terms of time. In this paper, it is aimed to determ...

With the rapid development of the Internet, thousands of different news reports from different channels are presented to us. So much news, particularly in the media sector, is an important question to be categorized and archived without human effort. In this study, it is aimed to be able to determine which news item belongs to large news headlines...

The classification of the emotions contained in the social media is of great importance in terms of its use in related fields such as media as well as developing technology. The Latent Dirichlet Allocation (LDA), a topic modeling algorithm, was used to determine which emotions the tweets on Twitter had in the study. Dataset consists of angry, fear,...