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SOCYVIA/README.md

SOCYVIA

Scientific Experimentation for Computational Social Science

DOI

DOI: 10.5281/zenodo.22135414

SOCYVIA is a bilingual Arabic/English research software environment for designing and running structured experiments in computational social science.

It brings experimental study design, participant workflows, questionnaires, behavioral data collection, deterministic analysis, reporting, and participant-facing research experiences into a single desktop environment.

Current release: SOCYVIA Desktop 1.0.0
Platforms: Windows · macOS · Linux

🌐 Official website: https://socyvia.com
📥 Downloads: https://socyvia.com/en/downloads
📖 Documentation: https://socyvia.com/en/docs


Why SOCYVIA?

Computational social science experiments often require researchers to combine multiple disconnected tools for study configuration, participant exposure, questionnaires, behavioral logging, analysis, reporting, and online deployment.

SOCYVIA is being developed as a research software environment that brings these stages into a more coherent experimental workflow.

The goal is not simply to provide another survey or analytics application, but to support structured scientific experimentation in which participant experiences, behavioral evidence, study conditions, and research outputs remain connected throughout the research process.


SOCYVIA Desktop 1.0

SOCYVIA 1.0 provides:

  • Experimental study design with groups, conditions, assignment, participant flow, and validation.
  • Text, media-source, and external-content workflows for participant stimuli.
  • Pre- and post-study questionnaires.
  • Session-linked behavioral data collection.
  • Deterministic scientific analysis and data-quality review.
  • Figures, research reports, and structured data exports.
  • Researcher-owned Cloudflare publication with canonical SOCYVIA participant links.
  • A shared SOCYVIA Participant Feed for demonstrations and published studies.
  • SOCYVIA AI product guidance and guarded interpretation of evidence computed by SOCYVIA.
  • Complete Arabic and English interfaces with RTL/LTR support.
  • Self-contained desktop distributions for Windows, macOS, and Linux.

Research Workflow

SOCYVIA is designed around an integrated experimental workflow:

Design → Configure → Publish → Participate → Collect → Analyze → Report

Researchers can structure experimental conditions and participant flows, collect questionnaire and behavioral evidence linked to research sessions, and produce structured outputs for subsequent scientific analysis and reporting.


Behavioral Research

SOCYVIA supports the collection of session-linked behavioral evidence generated during participant interaction with experimental experiences.

The platform is designed so that participant activity can remain connected to experimental conditions, questionnaires, and research sessions rather than being treated as isolated interaction data.


Participant Experiences

Studies can include participant-facing experiences based on:

  • Text
  • Media sources
  • External content
  • Questionnaires
  • Structured experimental flows

SOCYVIA also provides its Participant Feed for demonstrations and published research experiences.


Scientific Analysis

SOCYVIA 1.0 includes deterministic analysis capabilities designed to keep computed research evidence distinct from AI-assisted interpretation.

Researchers can work with:

  • Data-quality review
  • Deterministic analysis
  • Figures
  • Reports
  • Structured exports

SOCYVIA AI can provide product guidance and guarded interpretation of evidence already computed by SOCYVIA.


Arabic + English

SOCYVIA provides complete bilingual interfaces:

  • English — LTR
  • العربية — RTL

The bilingual interface is designed to make experimental research workflows more accessible to Arabic-speaking researchers while retaining an English research environment.


Platforms

Platform Distribution Current verification
Windows x64 Setup + Portable ZIP Physically verified on Windows; unsigned
macOS Apple Silicon Application ZIP Package verified; unsigned and not notarized; target-macOS QA required
macOS Intel Application ZIP Package verified; unsigned and not notarized; target-macOS QA required
Linux x64 AppImage + DEB + tar.gz Package verified; unsigned; target-Linux QA required

SHA-256 checksums accompany the public binary and archive artifacts.


Download SOCYVIA

The latest public release is available from:

SOCYVIA Downloads
https://socyvia.com/en/downloads

GitHub Releases
https://github.com/socyvia/SOCYVIA/releases/latest

Current release: SOCYVIA Desktop 1.0.0


Feedback & Issues

SOCYVIA 1.0 is the first public release.

Researchers, students, developers, and experimental-methods practitioners are encouraged to test the software and report:

  • Bugs
  • Usability problems
  • Experimental workflow limitations
  • Platform-specific issues
  • Documentation problems
  • Feature suggestions

Feedback can be submitted through GitHub Issues:

https://github.com/socyvia/SOCYVIA/issues

Real research use and critical feedback will help guide future development.


Coming in SOCYVIA 2.0

The planned SOCYVIA 2.0 roadmap extends the environment toward synchronized physiological and multimodal experimentation, including planned support for:

  • Eye Tracking
  • EEG
  • GSR
  • Lab Streaming Layer (LSL)

These capabilities are part of the planned 2.0 roadmap and are not features of SOCYVIA Desktop 1.0.


Project Status

SOCYVIA is under active development.

Version 1.0 establishes the first public behavioral experimentation environment. Future development will be informed by research use, reproducibility requirements, technical validation, and feedback from the scientific community.


Source Availability

SOCYVIA Desktop 1.0 is currently distributed as research software through official binary releases.

A community source strategy is being evaluated separately as the project develops. Binary availability should not currently be interpreted as an open-source release.


Developer

SOCYVIA is an independent research and technology initiative developed by Abdellah RIAD from methodological and experimental challenges encountered across media, sport, technology, and experimental research.

The project is being developed around the broader objective of making structured computational social science experimentation more accessible, coherent, and reproducible.


Links

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