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Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages
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In: Future Internet; Volume 14; Issue 3; Pages: 69 (2022)
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Study of the Yahoo-Yahoo Hash-Tag Tweets Using Sentiment Analysis and Opinion Mining Algorithms
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In: Information; Volume 13; Issue 3; Pages: 152 (2022)
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Deceptive Opinions Detection Using New Proposed Arabic Semantic Features
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In: ISSN: 1877-0509 ; EISSN: 1877-0509 ; Procedia Computer Science ; https://hal.archives-ouvertes.fr/hal-03299022 ; Procedia Computer Science, Elsevier, 2021, 189, pp.29 - 36. ⟨10.1016/j.procs.2021.05.067⟩ (2021)
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Sentiment Analysis of Arabic Documents
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In: Natural Language Processing for Global and Local Business ; https://hal.archives-ouvertes.fr/hal-03124729 ; Fatih Pinarbasi; M. Nurdan Taskiran. Natural Language Processing for Global and Local Business, pp.307-331, 2021, 9781799842408. ⟨10.4018/978-1-7998-4240-8.ch013⟩ ; https://www.igi-global.com/ (2021)
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| 5 |
The Role of Inferences in Opinion Mining : Applications to Chinese Social Media ; Le rôle des inférences pour la fouille d'opinion : applications aux réseaux sociaux en langue chinoise
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In: https://tel.archives-ouvertes.fr/tel-03469568 ; Linguistique. Institut National des Langues et Civilisations Orientales- INALCO PARIS - LANGUES O', 2021. Français. ⟨NNT : 2021INAL0016⟩ (2021)
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| 6 |
On Multi-domain Sentence Level Sentiment Analysis for Roman Urdu ...
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The Role of Inferences in Opinion Mining : Applications to Chinese Social Media ; Le rôle des inférences pour la fouille d'opinion : applications aux réseaux sociaux en langue chinoise
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In: https://tel.archives-ouvertes.fr/tel-03469568 ; Linguistique. Institut National des Langues et Civilisations Orientales- INALCO PARIS - LANGUES O', 2021. Français. ⟨NNT : 2021INAL0016⟩ (2021)
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| 8 |
A Survey on Sentiment Analysis and Opinion Mining in Greek Social Media
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In: Information ; Volume 12 ; Issue 8 (2021)
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Abstract:
As the amount of content that is created on social media is constantly increasing, more and more opinions and sentiments are expressed by people in various subjects. In this respect, sentiment analysis and opinion mining techniques can be valuable for the automatic analysis of huge textual corpora (comments, reviews, tweets etc.). Despite the advances in text mining algorithms, deep learning techniques, and text representation models, the results in such tasks are very good for only a few high-density languages (e.g., English) that possess large training corpora and rich linguistic resources ; nevertheless, there is still room for improvement for the other lower-density languages as well. In this direction, the current work employs various language models for representing social media texts and text classifiers in the Greek language, for detecting the polarity of opinions expressed on social media. The experimental results on a related dataset collected by the authors of the current work are promising, since various classifiers based on the language models (naive bayesian, random forests, support vector machines, logistic regression, deep feed-forward neural networks) outperform those of word or sentence-based embeddings (word2vec, GloVe), achieving a classification accuracy of more than 80%. Additionally, a new language model for Greek social media has also been trained on the aforementioned dataset, proving that language models based on domain specific corpora can improve the performance of generic language models by a margin of 2%. Finally, the resulting models are made freely available to the research community.
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Keyword:
Bidirectional Encoder Representations from Transformers; Greek social media; opinion mining; sentiment analysis; text embeddings; transformers
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URL: https://doi.org/10.3390/info12080331
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| 9 |
Sentiment-Target Word Pair Extraction Model Using Statistical Analysis of Sentence Structures
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In: Electronics; Volume 10; Issue 24; Pages: 3187 (2021)
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| 10 |
Analyzing Tweets to Rank FIFA Players using Named Entity Recognition ...
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| 11 |
Analyzing Tweets to Rank FIFA Players using Named Entity Recognition ...
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| 13 |
On Multi-domain Sentence Level Sentiment Analysis for Roman Urdu
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| 14 |
This! Identifying new sentiment slang through orthographic pleonasm online: Yasss slay gorg queen ilysm
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In: 36 ; 4 ; 114 ; 120 (2021)
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| 15 |
Inference Annotation of a Chinese Corpus for Opinion Mining
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In: LREC ; https://hal-inalco.archives-ouvertes.fr/hal-02507170 ; LREC, May 2020, Marseille, France (2020)
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| 16 |
Using Twitter Streams for Opinion Mining: a case study on Airport Noise
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In: ISSN: 1865-0929 ; Communications in Computer and Information Science ; https://hal.archives-ouvertes.fr/hal-03018998 ; Communications in Computer and Information Science, Springer Verlag, 2020, ⟨10.1007/978-3-030-44900-1_10⟩ (2020)
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| 17 |
Classifying User Experience based on the Intention to Communicate.
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In: ISSN: 1548-0992 ; IEEE Latin America Transactions ; https://hal.archives-ouvertes.fr/hal-03550858 ; IEEE Latin America Transactions, Institute of Electrical and Electronics Engineers, 2020, 18 (8), pp.1337-1344 (2020)
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| 18 |
An Enhanced Corpus for Arabic Newspapers Comments
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In: ISSN: 1683-3198 ; International Arab Journal of Information Technology ; https://hal.archives-ouvertes.fr/hal-03124728 ; International Arab Journal of Information Technology, Colleges of Computing and Information Society (CCIS), 2020, 17 (5), pp.789-798. ⟨10.34028/iajit/17/5/12⟩ (2020)
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| 19 |
Inference Annotation of a Chinese Corpus for Opinion Mining
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In: LREC ; https://hal-inalco.archives-ouvertes.fr/hal-02507170 ; LREC, May 2020, Marseille, France (2020)
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| 20 |
Improving Sentiment Polarity Detection through Target Identification
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