相关论文: Deep Learning Approach for Enhanced Cyber Threat I…
Social network analysis is an important problem in data mining. A fundamental step for analyzing social networks is to encode network data into low-dimensional representations, i.e., network embeddings, so that the network topology…
Many cyber network defense tools rely on the National Vulnerability Database (NVD) to provide timely information on known vulnerabilities that exist within systems on a given network. However, recent studies have indicated that the NVD is…
A novel Twitter context aided content caching (TAC) framework is proposed for enhancing the caching efficiency by taking advantage of the legibility and massive volume of Twitter data. For the purpose of promoting the caching efficiency,…
This paper presents a multidisciplinary approach to analyzing data from Telegram for early warning information regarding cyber threats. With the proliferation of hacktivist groups utilizing Telegram to disseminate information regarding…
This paper is to explore the possibility to use alternative data and artificial intelligence techniques to trade stocks. The efficacy of the daily Twitter sentiment on predicting the stock return is examined using machine learning methods.…
Climate change is one of the most pressing challenges of the 21st century, sparking widespread discourse across social media platforms. Activists, policymakers, and researchers seek to understand public sentiment and narratives while access…
Social media channels, such as Facebook, Twitter, and Instagram, have altered our world forever. People are now increasingly connected than ever and reveal a sort of digital persona. Although social media certainly has several remarkable…
Gang-involved youth in cities such as Chicago sometimes post on social media to express their aggression towards rival gangs and previous research has demonstrated that a deep learning approach can predict aggression and loss in posts. To…
Recent advancements in pre-trained language models have enabled convenient methods for generating human-like text at a large scale. Though these generation capabilities hold great potential for breakthrough applications, it can also be a…
Detecting cyber-anomalies and attacks are becoming a rising concern these days in the domain of cybersecurity. The knowledge of artificial intelligence, particularly, the machine learning techniques can be used to tackle these issues.…
The concern regarding users' data privacy has risen to its highest level due to the massive increase in communication platforms, social networking sites, and greater users' participation in online public discourse. An increasing number of…
In this contribution, we develop an accurate and effective event detection method to detect events from a Twitter stream, which uses visual and textual information to improve the performance of the mining process. The method monitors a…
Real-time social media data can provide useful information on evolving hazards. Alongside traditional methods of disaster detection, the integration of social media data can considerably enhance disaster management. In this paper, we…
Today, the internet is an integral part of our daily lives, enabling people to be more connected than ever before. However, this greater connectivity and access to information increase exposure to harmful content such as cyber-bullying and…
Social media platforms have revolutionized traditional communication techniques by enabling people globally to connect instantaneously, openly, and frequently. People use social media to share personal stories and express their opinion.…
We study the impact of neural networks in text classification. Our focus is on training deep neural networks with proper weight initialization and greedy layer-wise pretraining. Results are compared with 1-layer neural networks and Support…
The integration of communication networks and the Internet of Things (IoT) in Industrial Control Systems (ICSs) increases their vulnerability towards cyber-attacks, causing devastating outcomes. Traditional Intrusion Detection Systems…
Through anonymisation and accessibility, social media platforms have facilitated the proliferation of hate speech, prompting increased research in developing automatic methods to identify these texts. This paper explores the classification…
In recent years, people spend a lot of time on social networks. They use social networks as a place to comment on personal or public events. Thus, a large amount of information is generated and shared daily in these networks. Using such a…
Social media is a popular platform for timely information sharing. One of the important challenges for social media platforms like Twitter is whether to trust news shared on them when there is no systematic news verification process. On the…