Various data and coding projects. Let me know what you think!
The project uses Wikipedia data on U.S. far-right extremists and organizations as a proxy for public awareness on the topic. With temporal analysis, development of the network shows the growth of public attention on national security concerns, allowing for comparative analysis between types of extremism and seeking to better understand public knowledge as a factor for agenda setting and policy making. The first attempt presented here is an experimental approach to collecting and processing publicly available Wikipedia data around 18 far-right activists.
Not only after the killing of Walther Lübcke, the terror attack on a synagoge in Halle and the shooting spree in Hanau is far-right, anti-Semitic and anit-refugee crime surging in Germany. NGOs and journalists are cooperating to give a more granular picture of these hate crimes throughout Germany. Based on ~6,900 observation from the "arvig" dataset (2014 - today) and ~16,000 observations of "tatort rechts" (rechte gewalt, rege) dataset (2000 - today), this R-based ShinyApp visualized individual and county level data. I expanded the aggregation on the county level with an 600-variable panel dataset on demographics, social and economic factors from the German Federal Bureau of Statistics.
"CYsyphus" (pronounced SIGH-si-fis) is a decision-support tool, that provides users with an easy-to-search online database on existing cyber reports and recommendations. CYsyphus facilitates the discovery of past wisdom to avoid repetition and enable leapfrogging to new insights and recommendations in support of policy makers, congressional staffers, journalists and students. The project uses NLP-driven classification and categorization algorithms to corroborate and expand the existing collection of approx. 1,200 recommendations from 130 reports.
All-source intelligence analysts need improved modeling, analytic tools, and data visualization in order to understand dense urban areas and enhance situational awareness more effectively. POLassist helps you understand location data in an urban areas to improve situational awareness and response allocation. The POLassist prototype was developed as part of "Hacking4Defense" at Columbia University in the City of New York, 2020.
Displayed nodes represent users, channels, and guilds. Guilds in Discord represent an isolated collection of users and channels, and are often referred to as "servers". Users can participate in several guilds and communicate within channels by exchanging messages. Channels subgroup guilds into different streams (e.g., "meme boards", "shitposting", "help desks" etc.). Edges are retrieved actual messages sent from users. Data from DDoSecret. Thanks!
The visualization shows the interaction of Iron March forum members with more than 10 private messages exchanged. Red nodes symbolize a detected reference to German, set via the following criteria: German email address, German IP address, German forum posts (advanced to fluent skill level), German private messages (advanced to fluent skill level).
This Google Apps Script links a Telegram bot to a google spreadsheet and allows command-based information storing. Feed your Telegram bot with information to store in Google Spreadsheet. Indicate type of stored information with Telegram commands (starting with '/'), e.g. keywords, persons, locations. The bot stores URLs as HTML in your Google Drive folder.Best of all: Open Source / Open Code, Easy to install, free of charge, 24/7 readiness!
This TwitterUrlCrawler bot allows you to pull tweets from your feed or other users' timeline and store attached URLs in a Google Spreadsheet. Everything is managed with a Telegram bot, so you only save what is really interesting to your. It has never been easier to keep track of all the interesting URLs on Twitter out there. Check it out!