Related papers: Turkish Sentiment Analysis Using Machine Learning …
Extracting useful information for sentiment analysis and classification problems from a big amount of user-generated feedback, such as restaurant reviews, is a crucial task of natural language processing, which is not only for customer…
The Internet has become an essential tool for people in the modern world. Humans, like all living organisms, have essential requirements for survival. These include access to atmospheric oxygen, potable water, protective shelter, and…
Many people use Yelp to find a good restaurant. Nonetheless, with only an overall rating for each restaurant, Yelp offers not enough information for independently judging its various aspects such as environment, service or flavor. In this…
Artificial intelligence and machine learning have significantly bolstered the technological world. This paper explores the potential of transfer learning in natural language processing focusing mainly on sentiment analysis. The models…
Since internet technologies have advanced, one of the primary factors in company development is customer happiness. Online platforms have become prominent places for sharing reviews. Twitter is one of these platforms where customers…
Sentiment analysis of reviews is a popular task in natural language processing. In this work, the goal is to predict the score of food reviews on a scale of 1 to 5 with two recurrent neural networks that are carefully tuned. As for…
The aim of this study is to determine the perceived stress levels of 150 individuals and analyze the responses given to adapted questions in Turkish using machine learning. The test consists of 14 questions, each scored on a scale of 0 to…
Customer-provided reviews have become an important source of information for business owners and other customers alike. However, effectively analyzing millions of unstructured reviews remains challenging. While large language models (LLMs)…
Food reviews and recommendations have always been important for online food service websites. However, reviewing and recommending food is not simple as it is likely to be overwhelmed by disparate contexts and meanings. In this paper, we use…
Today's business ecosystem has become very competitive. Customer satisfaction has become a major focus for business growth. Business organizations are spending a lot of money and human resources on various strategies to understand and…
In this work, we predict the sentiment of restaurant reviews based on a subset of the Yelp Open Dataset. We utilize the meta features and text available in the dataset and evaluate several machine learning and state-of-the-art deep learning…
We use over 350,000 Yelp reviews on 5,000 restaurants to perform an ablation study on text preprocessing techniques. We also compare the effectiveness of several machine learning and deep learning models on predicting user sentiment…
Targeted Sentiment Analysis aims to extract sentiment towards a particular target from a given text. It is a field that is attracting attention due to the increasing accessibility of the Internet, which leads people to generate an enormous…
Large annotated datasets in NLP are overwhelmingly in English. This is an obstacle to progress in other languages. Unfortunately, obtaining new annotated resources for each task in each language would be prohibitively expensive. At the same…
In the era of rapid technological advancement, social media platforms such as Twitter (X) have emerged as indispensable tools for gathering consumer insights, capturing diverse opinions, and understanding public attitudes. This research…
Sentiment analysis aims to extract people's emotions and opinion from their comments on the web. It widely used in businesses to detect sentiment in social data, gauge brand reputation, and understand customers. Most of articles in this…
Artificial intelligence and natural language processing (NLP) are increasingly being used in customer service to interact with users and answer their questions. The goal of this systematic review is to examine existing research on the use…
In this study, we develop and assess new corpus selection and training methodologies to improve the effectiveness of Turkish language models. Specifically, we adapted Large Language Model generated datasets and translated English datasets…
The amount of textual data generation has increased enormously due to the effortless access of the Internet and the evolution of various web 2.0 applications. These textual data productions resulted because of the people express their…
Sentiment analysis is a widely researched area within Natural Language Processing (NLP), attracting significant interest due to the advent of automated solutions. Despite this, the task remains challenging because of the inherent complexity…