Evaluation of Accuracy Degradation Resulting from Concept Drift in a Fake News Detection System Using Emotional Expression
نویسندگان
چکیده
Fake news on social media has become a problem. refers to false information that is deliberately intended deceive people. Several studies have been conducted automatic detection systems reduce the damage caused by fake news. However, most address improvements made in accuracy, and real-world operations are rarely discussed. As contents expressions of change over time, model with high accuracy loses after few years. This phenomenon called concept drift. conventional methods employ word representations, these exhibit degradation resulting from changes fads usage. using sentiment words can identify inflammatory sentences, which characteristic news, may suppress performance In this study, vector representations obtained an emotion dictionary was compared embedding. Subsequently, we verified resistance degradation. The results revealed method representation less susceptible Models learning achieve both enable further development systems.
منابع مشابه
Concept drift detection in business process logs using deep learning
Process mining provides a bridge between process modeling and analysis on the one hand and data mining on the other hand. Process mining aims at discovering, monitoring, and improving real processes by extracting knowledge from event logs. However, as most business processes change over time (e.g. the effects of new legislation, seasonal effects and etc.), traditional process mining techniques ...
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 کاملConcept drift detection in event logs using statistical information of variants
In recent years, business process management (BPM) has been highly regarded as an improvement in the efficiency and effectiveness of organizations. Extracting and analyzing information on business processes is an important part of this structure. But these processes are not sustainable over time and may change for a variety of reasons, such as the environment and human resources. These changes ...
متن کاملFake News Detection using Stacked Ensemble of Classifiers
Fake news has become a hotly debated topic in journalism. In this paper, we present our entry to the 2017 Fake News Challenge which models the detection of fake news as a stance classification task that finished in 11th place on the leader board. Our entry is an ensemble system of classifiers developed by students in the context of their coursework. We show how we used the stacking ensemble met...
متن کاملConcept Drift Detection Using Online Bayesian Classifier
In data classification the goal is to predict the category of novel instances based on a collection of exemplars whose respective categories are known a priori. The state-of-theart includes various algorithms to solve this problem, including Naive Bayes, Random Forest, Support Vector Machines (SVM), among others. Most of these classifiers consider that the statistical data distribution remains ...
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: Applied sciences
سال: 2023
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app13106054