期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：9
页码：1-12
出版社：Science and Information Society (SAI)
摘要：Social media has recently become a basic source for
news consumption and sharing among millions of users. Social
media platforms enable users to publish and share their own
generated content with little or no restrictions. However, this
gives an opportunity for the spread of inaccurate or misleading
content, which can badly affect users’ beliefs and decisions. This
is why credibility assessment of social media content has recently
received tremendous attention. The majority of the studies in the
literature focused on identifying features that provide a high
predictive power when fed to data mining models and select the
model with the highest predictive performance given those
features. Results of these studies are conflicting regarding the
best model. Additionally, they disregarded the fact that real-time
credibility assessment is needed and thus time and resources
consumption is crucial for model selection. This study tries to fill
this gap by investigating the performance of different data
mining techniques for credibility assessments in terms of both
functional and operational characteristics for a balanced
evaluation that considers both model performance and
interoperability.
关键词：Data mining; performance evaluation; news
credibility; Twitter; social media
