Fake News Data Exploration and Analytics
نویسندگان
چکیده
Before the internet, people acquired their news from radio, television, and newspapers. With moved online, suddenly, anyone could post information on websites such as Facebook Twitter. The spread of fake has also increased with social media. It become one most significant issues this century. People use method to pollute reputation a well-reputed organization for benefit. important reason project is frame device examine language designs that describe right through machine learning. This paper proposes models learning can successfully detect news. These identify which real or specify accuracy said news, even in complex environment. After data-preprocessing exploration, we applied three models; random forest classifier, logistic regression, term frequency-inverse document frequency (TF-IDF) vectorizer. TFIDF vectorizer, decision tree classifier was approximately 99.52%, 98.63%, 99.63%, 99.68%, respectively. Machine be considered great choice find reality-based results other unstructured data various sentiment analysis applications.
منابع مشابه
Fake News in Social Networks
We model the spread of news as a social learning game on a network. Agents can either endorse or oppose a claim made in a piece of news, which itself may be either true or false. Agents base their decision on a private signal and their neighbors’ past actions. Given these inputs, agents follow strategies derived via multi-agent deep reinforcement learning and receive utility from acting in acco...
متن کاملCharacterizing Political Fake News in Twitter by its Meta-Data
This article presents a preliminary approach towards characterizing political fake news on Twitter through the analysis of their meta-data. In particular, we focus on more than 1.5M tweets collected on the day of the election of Donald Trump as 45th president of the United States of America. We use the meta-data embedded within those tweets in order to look for differences between tweets contai...
متن کاملAutomatic Detection of Fake News
The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content. In this paper, we focus on the automatic identification of fake content in online...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Electronics
سال: 2021
ISSN: ['2079-9292']
DOI: https://doi.org/10.3390/electronics10192326