Multi-source social media data sentiment analysis using bidirectional recurrent convolutional neural networks

Sentiment Analysis in Social Media Data for Depression Detection Using Artificial Intelligence: A Review

“…Word2Vec: Word2vec [11,14,38,44,53,56,65] a neural network model will be used to learn associations of words from a large corpus of text. A model can detect synonymous words or suggest additional words for a partial sentence, once trained.…”

“…GloVe: GloVe [11,14,[41][42][43]53], a unsupervised learning algorithm by mapping words into a meaningful space for obtaining words vector representations where the semantic similarity is related to the distance between words.…”

“…Features from the pre-processed data will be extracted using feature extraction techniques. In Fazeel Abid et al [14], Emoji's and emoticons is one the significant source of sentiments. A user on social networks expresses their feelings often using different kinds of emoji and emoticons.…”

“…Table 3 shows examples of emoticons. Like textual data, emoticons and emojis [3,9,11,14] also can be used for the sentiment analysis. They also have some sentiment score values, which can be considered or used for sentiment analysis.…”

Deep Sentiment Analysis: A Case Study on Stemmed Turkish Twitter Data

“…The RNN architecture is a type of DL algorithm that processes variable sequence of inputs using their internal states [72]. It allows a dynamic behavior derived from a feedforward neural network, which allows them to be applicable in miscellaneous tasks including speech [73], handwriting recognition [74], tumour detection with classification [75], network traffic analysis [76]- [78], text classification [79]- [82], and sentiment analysis [83]- [89].…”