PWEBSA: Twitter sentiment analysis by combining Plutchik wheel of emotion and word embedding

Exploring Word Embedding for Bangla Sentiment Analysis

2018 International Conference on Bangla Speech and Language Processing (ICBSLP) ◽

10.1109/icbslp.2018.8554443 ◽

2018 ◽

Cited By ~ 3

Author(s):

Sakhawat Hosain Sumit ◽

Md. Zakir Hossan ◽

Tareq Al Muntasir ◽

Tanvir Sourov

Keyword(s):

Sentiment Analysis ◽

Word Embedding

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A Comparative Study on Sentiment Analysis Influencing Word Embedding Using SVM and KNN

10.1007/978-981-16-4284-5_18 ◽

2021 ◽

pp. 199-211

Author(s):

Bachchu Paul ◽

Sanchita Guchhait ◽

Tanushree Dey ◽

Debashri Das Adhikary ◽

Somnath Bera

Keyword(s):

Comparative Study ◽

Sentiment Analysis ◽

Word Embedding

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Turkish tweet sentiment analysis with word embedding and machine learning

2017 25th Signal Processing and Communications Applications Conference (SIU) ◽

10.1109/siu.2017.7960195 ◽

2017 ◽

Cited By ~ 5

Author(s):

Deger Ayata ◽

Murat Saraclar ◽

Arzucan Ozgur

Keyword(s):

Machine Learning ◽

Sentiment Analysis ◽

Word Embedding

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Optimizing Word Embedding for Fine-Grained Sentiment Analysis

Lecture Notes in Computer Science - Artificial Intelligence and Security ◽

10.1007/978-3-030-24265-7_24 ◽

2019 ◽

pp. 275-286 ◽

Cited By ~ 1

Author(s):

Wei Zhang ◽

Yue Zhang ◽

Kehua Yang

Keyword(s):

Sentiment Analysis ◽

Word Embedding ◽

Fine Grained

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Integrating Terminology Extraction and Word Embedding for Unsupervised Aspect Based Sentiment Analysis

Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018 ◽

10.4000/books.aaccademia.3297 ◽

2018 ◽

pp. 176-181

Author(s):

Luca Dini ◽

Paolo Curtoni ◽

Elena Melnikova

Keyword(s):

Sentiment Analysis ◽

Word Embedding ◽

Terminology Extraction

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IMPLEMENTASI PROBABILISTIC NEURAL NETWORK DAN WORD EMBEDDING UNTUK ANALISIS SENTIMEN VAKSIN SINOVAC

Jurnal Responsif : Riset Sains dan Informatika ◽

10.51977/jti.v3i2.588 ◽

2021 ◽

Vol 3 (2) ◽

pp. 233-242

Author(s):

Abdul Rahman Wahid Rapsanjani ◽

Erfian Junianto

Keyword(s):

Neural Network ◽

Sentiment Analysis ◽

Probabilistic Neural Network ◽

Word Embedding

Penelitian ini bertujuan melakukan implementasi Probabilistic neural network dan Word Embedding dalam kasus sentiment analysis tentang tanggapan masyarakat tentang pemberian vaksin sinovac yangg diunggah di Twitter dan 3 class:positif, negative dan netral. Metode yang dipilih adalah metode klasifikasi Probabilistic Neural Network. Sebelum melakukan klasifikasi, praprocessing pada penelitian ini meliputi tokenizasi, normalisasi, menghilangkan emoticon, Convert Negasi, Stemming, Stopword Removal serta Word embedding. dataset yang digunakan berjumlah 1177 dataset dengan pembagiannya yaitu 560 dataset positif, 355 dataset negative dan 262 dataset netral. Program dirancang menggunakan Bahasa pemrograman python dengan beberapa library seperti keras, tensorflow dan pandas. Akurasi yang didapatkan pada pelatihan menggunakan Probabilistic Neural Network sebesar 91%. Hasil pengujian adalah penelitian ini mampu melakukan sentiment analysis dengan kesalahan sebesar 9%.

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