Hamideh Hajiabadi
Biographic Data
| ID | 9699291 |
|---|---|
| NAME | Hamideh Hajiabadi |
| GIVEN NAMES | Hamideh |
| FAMILY NAME | Hajiabadi |
| SIGNATURE | HAJIABADI H |
| AFFILIATIONS | Karlsruhe Institute of Technology |
| ORCID | 0000-0002-5793-4563 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| 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…
No prominent works on this page.
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…
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) · Artificial Intelligence (1 work) · Big data (1 work) · Business (1 work) · Computer Science (1 work)