Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Samer Aoudi"'
Autor:
Mohammed Saleh, Thair Kdour, Azzeddine Ferrah, Hamad Ahmed, Saleel AP, Rula Azzawi, Mohammed Hassouna, Issam Hamdan, Samer Aoudi, Khaleefa Mohammed, Ammar Ali
Publikováno v:
2022 8th International Conference on Information Technology Trends (ITT).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02991e290a0908ca1b4c46c2b1493acc
https://doi.org/10.1109/itt56123.2022.9863970
https://doi.org/10.1109/itt56123.2022.9863970
Publikováno v:
2020 Seventh International Conference on Information Technology Trends (ITT).
At a big data level there are voluminous amounts of posts in Arabic that can be found on social media and on various product/service review sites. This provides a rich source of information at a number of levels that can be useful both commercially a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e6d510bb7ac93722be3a656c09d0e7f
https://doi.org/10.1109/itt51279.2020.9320774
https://doi.org/10.1109/itt51279.2020.9320774
Publikováno v:
ICSIE
In this paper, we describe a procedure for extracting annotated Arabic negative and positive tweets. We use these extracted annotated tweets to build our sentiment system using Naive Bayes with TF-IDF enhancement. The large size of training data for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba204b5a65bf22bb200689bfef53ccd8
https://doi.org/10.1145/3328833.3328874
https://doi.org/10.1145/3328833.3328874
Autor:
Samer Aoudi, Asif Malik
Publikováno v:
2018 Fifth HCT Information Technology Trends (ITT).
Due to the vast amount of digital information on social media, a platform like Twitter provides a rich corpus for data mining in general, and opinion mining and sentiment analysis in specific. Moreover, and since social data is mostly unstructured in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d0332c4ad817068e96822c33f5a3377
https://doi.org/10.1109/ctit.2018.8649509
https://doi.org/10.1109/ctit.2018.8649509
Autor:
Asif Malik, Samer Aoudi
Publikováno v:
2018 Fifth HCT Information Technology Trends (ITT).
The aim of this paper is to understand the chronological communication behavior of Twitter users immediately after the 2017 Iran-Iraq earthquake by identifying word frequencies and an overall sentiment analysis of their tweets. A total of 20000 tweet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6f2ffae6f6810c1d4a9f33f5068cfdf5
https://doi.org/10.1109/ctit.2018.8649501
https://doi.org/10.1109/ctit.2018.8649501