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21 st  Century   #Media Literacy
                                                                                                Skills
                           Video Session

                       Watch this video on "What is Sentiment analysis?" at the given link:
                       https://www.youtube.com/watch?v=5HQCNAsSO-s or scan the QR code and answer the
                       following question:
                       How does sarcasm affect sentiment analysis in a rule-based approach?







                         NLP with Orange Data Mining Tool


                 NLP with the Orange Data Mining Tool allows users to perform text preprocessing, topic modelling, and sentiment
                 analysis through an easy-to-use visual workflow interface. It simplifies natural language processing tasks without
                 requiring extensive programming knowledge.

                 Sentiment Analysis Methods


                 Sentiment Analysis Methods can be used to determine the sentiment expressed in a piece of text, such as a
                 review, comment, or social media post. It helps to identify whether the expressed sentiment is positive, negative,
                 or neutral. Some of the Sentiment Analysis methods are as follows:
                    • Liu Hu: It uses English and Slovenian languages. It utilises a lexicon-based approach for sentiment analysis. This
                   means it relies on predefined dictionaries of positive and negative words to determine sentiment.

                    • Vader (Valence Aware Dictionary and Sentiment Reasoner): It uses English language. It is a lexicon- and
                   rule-based method designed to capture both the intensity (valence) and polarity (positive, negative, neutral) of
                   sentiments in text.

                    • Multilingual Sentiment: It supports multiple languages. It is also lexicon-based, but focuses on accommodating
                   several languages for broader applicability.
                    • SentiArt: It uses English and German. It is based on vector space models, which are computational methods
                   representing words or phrases in multi-dimensional space, it computes the valence (emotional value) of text.

                    • Custom Dictionary: It allows users to define dictionaries with their own positive and negative terms. It offers
                   flexibility by enabling users to tailor sentiment dictionaries to specific contexts. The analysis follows Liu Hu's
                   computation method.


                                Reboot


                      1.  What NLP tasks can be performed using the Orange Data Mining Tool?


                      2.  What languages does SentiArt support for sentiment analysis?






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