Imran Nadeem

Zhengzhou University | zzu · School of Computer and Artificial Intelligence

Over the years, there has been a rise in the number of fabricated and fake news stories that utilize both textual and visual information formats. This coincides with the increased likelihood that users will acquire their news from websites and social media platforms. While there has been various research into the detection of fake news in text usin...

This article introduces a comprehensive methodology for mapping and assessing the urban built-up areas and establishing a spatial gross domestic product (GDP) model for Zhengzhou using night-time light (NTL) data, alongside socioeconomic statistical data from 2012 to 2017. Two supervised sorting algorithms, namely the support vector machine (SVM) a...

Greenfield investment is considered the backbone of emerging economies and developing countries. This research is carried out to investigate the causal impact of Greenfield investment as a target variable and some other controlled variables for the sample of 23 Latin American and Caribbean (LA&C) developing countries. The period is 1998–2017, and L...

Electricity theft is the largest type of non-technical losses faced by power utilities around the globe. It not only raises revenue losses to the utilities but also leads to lethal fires and electric shocks at distribution side. In the past, field operation groups were sent by the utilities to conduct inspections of suspicions electric equipments s...

Aspect-based sentiment analysis refers to the task of determining the sentiment polarity associated with particular aspects mentioned in a sentence or document. Previous studies have used attention-based neural network models to connect aspect terms with context words, but these models often perform poorly due to limited interaction between aspect...

The task of analyzing sentiment has been extensively researched for a variety of languages. However, due to a dearth of readily available Natural Language Processing methods, Urdu sentiment analysis still necessitates additional study by academics. When it comes to text processing, Urdu has a lot to offer because of its rich morphological structure...

News media agencies are known to publish misinformation, disinformation, and propaganda for the sake of money, higher news propagation, political influence, or other unfair reasons. The exponential increase in the use of social media has also contributed to the frequent spread of fake news. This study extends the concept of symmetry into deep learn...

Due to the illegal use of electricity, non-technical losses are exponentially increasing in electricity distribution systems day by day. With the debut of smart meters in the smart grid, new electricity theft attacks are welcomed. The investigation of abnormal electricity consumption patterns helps in detecting electricity thieves. Moreover, existi...

News media always pursue informing the public at large. It is impossible to overestimate the significance of understanding the semantics of news coverage. Traditionally, a news text is assigned to a single category; however, a piece of news may contain information from more than one domain. A multi-label text classification model for news is propos...

Due to the exponential increase in internet and social media users, fake news travels rapidly, and no one is immune to its adverse effects. Various machine learning approaches have evaluated text and images to categorize false news over time, but they lack a comprehensive representation of relevant features. This paper presents an automated method...

Sentiment analysis is an ongoing research field within the discipline of data mining. The majority of academics employ deep learning models for sentiment analysis due to their ability to self-learn and process vast amounts of data. However, the performance of deep learning models depends on the values of the hyperparameters. Determining suitable va...