Due to the extreme divergence of social discussions happening in the political space, rumours and fake news becoming inferno which is difficult for anyone who reads to differentiate it from the truth.
What we are going to achieve?
To detect the propagandas at article level, sentence level and recognizing its type.
Using supervised machine learning technique, model shall be created to identify and flag the false news propaganda.
This article describes our submission for the Hack the News Datathon 2019 which focuses on Task 2, Propaganda sentence classification. It outlines our exploratory data analysis, methodology and future work. Our work revolves around the BERT model as we believe it offers an excellent language model that’s also good at attending to context which is an important aspect of propaganda detection.
The Institute for Propaganda Analysis in 1938 defined propaganda as: “The expression of an opinion or an action by individuals or groups […]
The NSI case – Predicting Household Budgets by team Lemurs Team Tsvetan (cecopld) Radoslav (rdimitrov) (mr-reliable) (khadeer) Business Understanding The survey’s […]
In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write […]
In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write […]
In this article the mentors give some preliminary guidelines, advice and suggestions to the participants for the case. Every mentor should write […]
In this article, the mentors give some preliminary guidelines, advice, and suggestions to the participants for the case. Every mentor should write […]
This is a Leopards team’s submission for the Propaganda Detection datathon. Key findings: the best performing classifier is logistic regression, operating on Word2vec representations of the sentences plus several designed features like the proportion of sentiment-bearing words in the sentence.
The word propaganda is defined as designating any attempt to influence the opinions or actions of others to some predetermined end by appealing to their emotions or prejudices or by distorting the facts. We are fooled by propaganda chiefly because they appeal to our emotions rather than to our reason. They make us believe and do something we would not believe or do. And since it appeal more to our emotions; we often don’t recognize it when we see it.
The current political landscape is shaped by extreme polarization of opinions and by the proliferation of fake news.
Studies and surveys has found that rumour’s and fake news tend to spread six times faster than truthful information. This situation both damages the reputation of respectable news outlets and it also undermines the very foundations of democracy, which needs free and reliable press to thrive. Therefore, it is in the interest of the public as well as of the news organizations to be able to detect and fight disinformation in all its forms.
Here, we are trying to create a tool that can help identify propagandistic articles with the help of Predictive Analytics.
The main objectives are:
(i) to flag the article as a whole
(ii) to detect the potentially propagandistic sentences in a news article
(iii) to identify the exact type and span of use of propagandistic techniques
Edit: link to github is here: https://github.com/mboyanov/propaganda-deteciton Article
