Hamed Vahdat-Nejad
Biographic Data
| ID | 8547809 |
|---|---|
| NAME | Hamed Vahdat-Nejad |
| GIVEN NAMES | Hamed |
| FAMILY NAME | Vahdat-Nejad |
| SIGNATURE | VAHDAT-NEJAD H |
| AFFILIATIONS | University of Birjand |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Enhancing tourism sentiment analysis with deep learning
Sentiment analysis plays a crucial role in extracting valuable insights from tourists reviews. Existing sentiment analysis techniques designed for general text often fall short when applied to tourism-related comments. This paper proposes an innovative deep learning-based approach for analysing comments in tourism. We utilise a BERT-based word embedding technique to capture vector representations of each preprocessed tweet. We use three deep lear…
Covid-19 and tourism
Taking advantage of the users’ posts on Twitter, we investigate the impact of COVID-19 on tourism in the early months of the epidemic. For this purpose, more than two million tweets published in the first months of the outbreak are analyzed. A comprehensive lexicon of keywords in the field of tourism, as well as international airlines, is collected and used for extracting tourism-related tweets. Employing a new model based on the RoBERTa language…
Detecting overlapping communities in LBSNs by fuzzy subtractive clustering
No prominent works on this page.
Detecting overlapping communities in LBSNs by fuzzy subtractive clustering
Covid-19 and tourism
Taking advantage of the users’ posts on Twitter, we investigate the impact of COVID-19 on tourism in the early months of the epidemic. For this purpose, more than two million tweets published in the first months of the outbreak are analyzed. A comprehensive lexicon of keywords in the field of tourism, as well as international airlines, is collected and used for extracting tourism-related tweets. Employing a new model based on the RoBERTa language…
Enhancing tourism sentiment analysis with deep learning
Sentiment analysis plays a crucial role in extracting valuable insights from tourists reviews. Existing sentiment analysis techniques designed for general text often fall short when applied to tourism-related comments. This paper proposes an innovative deep learning-based approach for analysing comments in tourism. We utilise a BERT-based word embedding technique to capture vector representations of each preprocessed tweet. We use three deep lear…
Artificial Intelligence (2 works) · Computer Science (2 works) · Digital Marketing and Social Media (2 works) · Sentiment analysis (2 works) · Sentiment Analysis and Opinion Mining (2 works) · Tourism (2 works) · 2019-20 coronavirus outbreak (1 work) · Advertising (1 work) · Big data (1 work) · Business (1 work)