Posted 4 CommentsPosted in News

Excerpt: Big data has become a household name for businesses nowadays. It has become an integral part of all sorts of businesses, especially for those enterprises that leverage data to gather insights. Data Science has become a meeting point for science and AI in this day and age. Even after the onset of the pandemic, the field has seen tremendous growth.

Datathon – HackNews – Solution – TEXT_MINERS

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Propaganda is a form of communication that is aimed at influencing the attitude of a community toward some cause or position. It often presents facts selectively to encourage a particular synthesis. The disinformation damages the reputation of respectable news outlets, organisations and very bad for business indeed. The objective of the Hackathon is to be able to detect the Propaganda and Non-propaganda news as well as to develop a model that can help with the venture. The other objectives of this work includes detecting phrases which are propagandist and also finding out the type of propaganda it is. The algorithms that we will be taking help from are Passive Aggressive, Multiple Layer Perceptron Network, Logistic Regression, AdaBoost, Decision Tree, Random Forest, KNN, SVM and Naive Bayes to detect the potentially propagandistic and non-propagandistic sentences in a news article. For the evaluation, we are calculating F1 Score to measure the class imbalance in the testing dataset. We have used the best model for detecting propagandist and non-propagandist articles, phrases and also type of propaganda.

“What’s in a Jargon?”

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Everyday we come across fancy jargon like data science, machine learning , artificial intelligence, computer vision, NLP, etc. You must have wondered as why terms like data science and AI are used together in names of research institutes like the Alan Turing Institute for Data Science and Artificial Intelligence. Does these two words mean the same ? Does it not? If it is same , why not club them into a single term , if not then why not have two different names instead of using them along side one another.