diff --git a/client/src/App.tsx b/client/src/App.tsx index a7e5a74..ce753e0 100644 --- a/client/src/App.tsx +++ b/client/src/App.tsx @@ -4,6 +4,7 @@ import Home from './pages/Home/Home' import ProjectView from './pages/ProjectView/ProjectView' import Project from './components/View/DataGrid/Project' import Overview from './pages/Dashboard/Overview' +import IC2S2 from './pages/IC2S2/IC2S2' function App() { return ( @@ -15,6 +16,7 @@ function App() { } /> } /> } /> + } /> ) diff --git a/client/src/pages/IC2S2/IC2S2.tsx b/client/src/pages/IC2S2/IC2S2.tsx new file mode 100644 index 0000000..76aa70a --- /dev/null +++ b/client/src/pages/IC2S2/IC2S2.tsx @@ -0,0 +1,237 @@ +import { useEffect, useRef } from 'react' +import { createUniverse } from '../Home/stars-render' + +const IC2S2 = () => { + const canvasRef = useRef(null) + + useEffect(() => { + const starDensity = 0.216 + const speedCoeff = 0.03 + const giantColor = '180,184,240' + const starColor = '226,225,142' + const cometColor = '226,225,224' + const cometDisabled = false + const canvas = canvasRef.current + if (!canvas) return + + const cleanup = createUniverse( + canvas, + starDensity, + speedCoeff, + giantColor, + starColor, + cometColor, + cometDisabled, + ) + return () => { + cleanup() + } + }, []) + + return ( +
+ {/* Galaxy Background Canvas */} + + + {/* Fixed Navigation Menu */} + + + {/* Scrollable Content Sections */} +
+ {/* SECTION: Description */} +
+

Research Cartography with Atlas

+

+ In this workshop, you will learn about the conceptual importance and challenges of + research cartography and gain hands‑on practice using Atlas—our platform designed to + systematically analyze and integrate research findings across literature. Questions like + “Under which situations does X cause Y?” require consistently detailed comparisons + across studies. +

+

+ By emphasizing commensurability—describing findings in comparable ways—Atlas helps + reveal the actual practices behind reported claims and supports more effective + meta‑analysis. Sign up or log in to get started here:{' '} + + https://atlas.seas.upenn.edu + +

+

+ Join us on July 21‑24, 2025, in Norrköping, Sweden at the 11th International Conference + on Computational Social Science (IC²S²) to learn a new scientific approach that turns + research papers into quantitative maps. +

+
+ + {/* SECTION: Tutorial Outline */} +
+

Tutorial Outline

+
    +
  • + Introducing research cartography: A high‑level + overview of theory and practice (30–40 minutes). +
    • +
  • + Case study: A working demo illustrating + end‑to‑end data processing and project workflow (20–40 minutes). +
    • +
  • + Hands‑on with Atlas: Participants create a + project from scratch, add literature, select features, and run analyses (40 minutes). +
    • +
  • + Creating features on Atlas: A guided + brainstorming and discussion session focusing on key dimensions (20 minutes). +
    • +
  • + New feature in practice: Time for participants + to develop and test their own features (40 minutes). +
    • +
  • + Developer tooling: An introduction to API + access, deployment, and contributing to open‑source tools (10–20 minutes). +
    • +
+
+ + {/* SECTION: Hands‑On Session Material */} +
+

Hands‑On Session Material

+

+ During the hands‑on segment of the tutorial, participants will log in to Atlas and set + up their own research projects. The session will guide you through: +

+
    +
  • Importing and organizing research papers.
    • +
  • Selecting or even defining new dimensions (features) for systematic comparison.
    • +
  • + Running analyses and visualizing research maps that highlight key experimental + details. +
    • +
  • Exporting synthesized data to further your research.
    • +
+

+ Please bring your own list of papers (e.g., experiments with at least 10 subjects and + multiple conditions) and a laptop. +

+
+ + {/* SECTION: Speakers */} +
+

Speakers & Organizers

+ +
+ {/* Mark Whiting */} +
+

Mark Whiting

+

+ University of Pennsylvania, Pareto.ai –{' '} + markew@seas.upenn.edu +

+

+ Mark E. Whiting is the Chief Technology Officer of Pareto Inc and a visiting + scientist at the Computational Social Science Lab (CSSLab) at the University of + Pennsylvania. With postdoctoral experience with Duncan Watts at Penn and Michael S. + Bernstein at Stanford, Mark holds degrees in Design from RMIT and KAIST and a PhD in + Engineering from CMU. Learn more about him at{' '} + + https://whiting.me + + . +

+
+ + {/* Amirhossein Nakhaei */} +
+

Amirhossein Nakhaei

+

+ RWTH Aachen University –{' '} + amirhossein.nakhaei@rwth-aachen.de +

+

+ Amirhossein Nakhaei is an incoming PhD student in Data Science at Boston University + and a visiting researcher at CSSLab at Penn. Holding a master’s in Computational + Social Science from RWTH Aachen University, he currently applies his expertise as a + software engineer in Berlin. +

+
+ + {/* Linnea Gandhi */} +
+

Linnea Gandhi

+

+ University of Pennsylvania –{' '} + lgandhi@wharton.upenn.edu +

+

+ Linnea Gandhi is a Lecturer and PhD candidate at Wharton whose research focuses on + improving the generalizability of behavioral science interventions. Her + dissertation—supported by a database of 200+ experimental variables—seeks to both + predict new experiments and build LLM‑based tools to expedite research synthesis via + Atlas. +

+
+ + {/* Duncan Watts */} +
+

Duncan Watts

+

+ University of Pennsylvania –{' '} + djwatts@seas.upenn.edu +

+

+ Duncan J. Watts is the Stevens University Professor at the University of + Pennsylvania with primary appointments across several departments including + Communication, Engineering, and Operations. His research centers on social networks + and the dynamics of human systems, providing a critical foundation for the work + presented in this workshop. +

+
+
+
+
+
+ ) +} + +export default IC2S2