|
|
|
|
|
Shariq Shah, Hossein Ghomeshi, Edlira Vakaj, Emmett Cooper and Rasheed Mohammad
Human communication is predominantly expressed through speech and writing, which are powerful mediums for conveying thoughts and opinions. Researchers have been studying the analysis of human sentiments for a long time, including the emerging area of bim...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ashokkumar Palanivinayagam, Claude Ziad El-Bayeh and Robertas Dama?evicius
Machine-learning-based text classification is one of the leading research areas and has a wide range of applications, which include spam detection, hate speech identification, reviews, rating summarization, sentiment analysis, and topic modelling. Widely...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nirmalya Thakur, Yuvraj Nihal Duggal and Zihui Liu
In the last decade and a half, the world has experienced outbreaks of a range of viruses such as COVID-19, H1N1, flu, Ebola, Zika virus, Middle East Respiratory Syndrome (MERS), measles, and West Nile virus, just to name a few. During these virus outbrea...
ver más
|
|
|
|
|
|
|
|
|
|
|
Benedikt Badanik, Rebeka Remenysegova and Antonin Kazda
This paper focuses on the analysis of traditional methods of service quality evaluation and represents a new sentimental approach to airline service quality evaluation employing user-generated content. It identifies aspects of airline service that passen...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nirmalya Thakur, Kesha A. Patel, Audrey Poon, Rishika Shah, Nazif Azizi and Changhee Han
Exoskeletons have emerged as a vital technology in the last decade and a half, with diverse use cases in different domains. Even though several works related to the analysis of Tweets about emerging technologies exist, none of those works have focused on...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shangyi Yan, Jingya Wang and Zhiqiang Song
To address the shortcomings of existing deep learning models and the characteristics of microblog speech, we propose the DCCMM model to improve the effectiveness of microblog sentiment analysis. The model employs WOBERT Plus and ALBERT to dynamically enc...
ver más
|
|
|
|
|
|
|
|
|
|
|
Krzysztof Fiok, Waldemar Karwowski, Edgar Gutierrez, Tameika Liciaga, Alessandro Belmonte and Rocco Capobianco
Volcanoes of hate and disrespect erupt in societies often not without fatal consequences. To address this negative phenomenon scientists struggled to understand and analyze its roots and language expressions described as hate speech. As a result, it is n...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kai-Xu Han, Wei Chien, Chien-Ching Chiu and Yu-Ting Cheng
At present, in the mainstream sentiment analysis methods represented by the Support Vector Machine, the vocabulary and the latent semantic information involved in the text are not well considered, and sentiment analysis of text is dependent overly on the...
ver más
|
|
|
|
|
|
|
|
|
|
|
Luana Balador Belisário, Luiz Gabriel Ferreira and Thiago Alexandre Salgueiro Pardo
Texts published on social media have been a valuable source of information for companies and users, as the analysis of this data helps improving/selecting products and services of interest. Due to the huge amount of data, techniques for automatically ana...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ayse Giz Gulnerman and Himmet Karaman
The data generated by social media such as Twitter are classified as big data and the usability of those data can provide a wide range of resources to various study areas including disaster management, tourism, political science, and health. However, apa...
ver más
|
|
|
|
|
|