Journal ArticleDOI
Heuristic-Assisted BERT for Twitter Sentiment Analysis
TLDR
The identification of opinions and sentiments from tweets is termed as "Twitter Sentiment Analysis (TSA)" as mentioned in this paper and the major process of TSA is to determine the sentiment or polarity of the tweet and then c...Abstract:
The identification of opinions and sentiments from tweets is termed as “Twitter Sentiment Analysis (TSA)”. The major process of TSA is to determine the sentiment or polarity of the tweet and then c...read more
Citations
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Journal ArticleDOI
A novel unsupervised ensemble framework using concept-based linguistic methods and machine learning for twitter sentiment analysis
Maryum Bibi,Wajid Arshad Abbasi,Wajid Aziz,Sundus Shoki Khalil,Mueen Uddin,Celestine Iwendi,Thippa Reddy Gadekallu +6 more
TL;DR: In this paper , a novel unsupervised learning framework based on concept-based and hierarchical clustering is proposed for Twitter sentiment analysis, and two different feature representation methods including Boolean and Term frequency-inverse document frequency (TF-IDF) are investigated.
Journal ArticleDOI
Weibo Text Sentiment Analysis Based on BERT and Deep Learning
TL;DR: Wang et al. as discussed by the authors proposed a new model based on BERT and deep learning for Weibo text sentiment analysis, which used BERT to represent the text with dynamic word vectors and using the processed sentiment dictionary to enhance the sentiment features of the vectors; then adopting the BiLSTM to extract the contextual features of text, the processed vector representation is weighted by the attention mechanism.
Journal ArticleDOI
(Re)shaping online narratives: when bots promote the message of President Trump during his first impeachment
Michael C. Galgoczy,Atharva Yashodhan Phatak,C. Danielle Vinson,Vijay Mago,Philippe J. Giabbanelli +4 more
TL;DR: In this paper , the role of bots in the first impeachment of former president Donald Trump was examined. But their work focused on manually examining a relatively few tweets to emphasize rhetoric, or the use of Natural Language Processing (NLP) of a much larger corpus with respect to common metrics such as sentiment.
Journal ArticleDOI
Customer Sentiment Recognition in Conversation Based on Contextual Semantic and Affective Interaction Information
TL;DR: In this article , a conversational sentiment analysis method based on contextual semantic and affective interaction information is proposed, which uses different bidirectional gated recurrent unit (BiGRU) combined with attention mechanisms to encode the contextual semantic information of different types of conversational texts.
Journal ArticleDOI
College English Intercultural Teaching Strategies Based on Network Construction under the Concept of Teaching to the Future
TL;DR: Based on the SPOC teaching model, the authors constructs a new cross-cultural teaching model for college English and conducts experiments on two selected classes of the same grade in a university, which shows that students increase their interest in learning English culture and enhance their ability to communicate and collaborate.
References
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The Whale Optimization Algorithm
Seyedali Mirjalili,Andrew Lewis +1 more
TL;DR: Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods.
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A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm
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Genetic algorithms for modelling and optimisation
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Journal ArticleDOI
Deep Convolution Neural Networks for Twitter Sentiment Analysis
TL;DR: A word embeddings method obtained by unsupervised learning based on large twitter corpora is introduced, this method using latent contextual semantic relationships and co-occurrence statistical characteristics between words in tweets to form a sentiment feature set of tweets.
Journal ArticleDOI
Emotion and sentiment analysis from Twitter text
TL;DR: The target of the work described in this paper is to detect and analyze sentiment and emotion expressed by people from text in their twitter posts and use them for generating recommendations.