Tag: basics of sentiment analysis

The overwhelming volume of social media data has created complex challenges for digital governance and policy-making, particularly in identifying and addressing social bias embedded in online discourse.

Fine-tuning a pre-trained model involves taking a model already trained on a large, general dataset and adapting it to perform well on a smaller, specific task dataset. Transformers is a library of several pre-trained large language models (LLMs) available as open source for training and inference (Hugging Face, n.d.-b). Transformer models are language models that […]

The Valence Aware Dictionary and Sentiment Reasoner (VADER) is a lexicon-based sentiment analysis tool that uses a lexicon dictionary to assign predefined sentiment scores.

Rule-based sentiment analysis is a pragmatic choice for specific use cases, especially where transparency, speed, or cost matter.

Lexical normalisation is the process of converting noisy, informal, or misspelled text into its standardized form.

Sentiment analysis helps to detect different emotions like happiness, anger, or sadness in a phrase or text like product review, feedback, comments or opinions in a social network.