Social media platforms have become a hub for political activities and discussions, democratizing participation in these endeavors. However, they have also become an incubator for manipulation campaigns, like information operations (IOs). Some social media platforms have released datasets related to such IOs originating from different countries. However, we lack comprehensive control data that can enable the development of IO detection methods. To bridge this gap, we present new labeled datasets about 26 campaigns, which contain both IO posts verified by a social media platform and over 13M posts by 303k accounts that discussed similar topics in the same time frames (control data). The datasets will facilitate the study of narratives, network interactions, and engagement strategies employed by coordinated accounts across various campaigns and countries. By comparing these coordinated accounts against organic ones, researchers can develop and benchmark IO detection algorithms.

We present 3DLNews, a novel dataset with local news articles from the United States spanning the period from 1996 to 2024. It contains almost 1 million URLs (with HTML text) from over 14,000 local newspapers, TV, and radio stations across all 50 states, and provides a broad snapshot of the US local news landscape. The dataset was collected by scraping Google and Twitter search results. We employed a multi-step filtering process to remove non-news article links and enriched the dataset with metadata such as the names and geo-coordinates of the source news media organizations, article publication dates, etc. Furthermore, we demonstrated the utility of 3DLNews by outlining four applications.

The vastness of the web imposes a prohibitive cost on building large-scale search engines with limited resources. Crawl frontiers thus need to be optimized to improve the coverage and freshness of crawled content. In this paper, we propose an approach for modeling the dynamics of change in the web using archived copies of webpages. To evaluate its utility, we conduct a preliminary study on the scholarly web using 19,977 seed URLs of authors’ homepages obtained from their Google Scholar profiles. We first obtain archived copies of these webpages from the Internet Archive (IA), and estimate when their actual updates occurred. Next, we apply maximum likelihood to estimate their mean update frequency (λ) values. Our evaluation shows that λ values derived from a short history of archived data provide a good estimate for the true update frequency in the short-term, and that our method provides better estimations of updates at a fraction of resources compared to the baseline models. Based on this, we demonstrate the utility of archived data to optimize the crawling strategy of web crawlers, and uncover important challenges that inspire future research directions.

MOTIVATION: As the mean age of parenthood grows, the effect of parental age on genetic disease and child health becomes ever more important. A number of autosomal dominant disorders show a dramatic paternal age effect due to selfish mutations: substitutions that grant spermatogonial stem cells (SSCs) a selective advantage in the testes of the father, but have a deleterious effect in offspring. In this paper we present a computational technique to model the SSC niche in order to examine the phenomenon and draw conclusions across different genes and disorders. RESULTS: We used a Markov chain to model the probabilities of mutation and positive selection with cell divisions. The model was fitted to available data on disease incidence and also mutation assays of sperm donors. Strength of selective advantage is presented for a range of disorders including Apert's syndrome and achondroplasia. Incidence of the diseases was predicted closely for most disorders and was heavily influenced by the site-specific mutation rate and the number of mutable alleles. The model also successfully predicted a stronger selective advantage for more strongly activating gain-of-function mutations within the same gene. Both positive selection and the rate of copy-error mutations are important in adequately explaining the paternal age effect. AVAILABILITY AND IMPLEMENTATION: C ++/R source codes and documentation including compilation instructions are available under GNU license at https://github.com/anwala/NicheSimulation CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.

Teaching information security courses is technically challenging. In an information security course, students and instructors often end up struggling in low-level and complicated software installation, system setup, service configuration, command operations, and data manipulation while losing concentration in learning the important information security principles. To help students in information security courses learn information security principles more effectively and efficiently, we used the workflow technology to create scenario-based workflows in order to improve the effectiveness of teaching and learning of several key information security principles and techniques. Two case studies simulating real-life scenarios, including one for an online banking system and one for an online grading system, are recreated within a laboratory setting using workflow technology and are then presented in information security classes. Our educational practice shows that the benefits of using workflow technology in information security education have been well received by students.