Research Preparation: Difference between revisions

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5. [https://canyoublockit.com/extreme-test/ AdBlock Test] - Ensure ads are blocked.
5. [https://canyoublockit.com/extreme-test/ AdBlock Test] - Ensure ads are blocked.


For more detailed guidance, see the full [[dfp-guide|Digital Force Protection Guide]].
See the full [[dfp-guide|Digital Force Protection Guide]] for more detailed guidance.


[[Category:Research]]
[[Category:Research]]

Latest revision as of 00:21, 6 October 2024

Plan and Prepare for Research

Plan for Research

Research templates are available for community members to use and edit.

Understanding the Topic or Tasks

  1. Clearly define the research topic or tasks to ensure the team is aligned on goals and deliverables.
  2. This could involve brainstorming sessions or mind mapping to explore different aspects of the research.
  3. Confirm the scope of the research and the specific questions or problems that need to be answered (e.g., identifying a company’s center of gravity, understanding a target audience, or analyzing a network for vulnerabilities).

Identify the Scope of the Research

  1. Define the boundaries of the research, including geographical area, time frame, and specific aspects of the topic to be covered.
  2. Determine specific objectives such as identifying key players, understanding behaviors, or forecasting risks.
  3. Identify research limitations like data availability, ethical considerations, or resource constraints.
  4. Define the research questions guiding the data collection and analysis process.

Identifying Necessary Data

  • Type of Data: Determine whether qualitative, quantitative, or a mix of both is needed. This decision will influence data collection methods.
  • Sources of Data: List potential sources like public databases, surveys, interviews, or experimental data.

Developing a Collection Strategy

  • Methods: Choose appropriate data collection methods like surveys, web scraping, direct observation, or experiments.
  • Tools: Identify any software or tools required for the collection, such as survey platforms or data logging equipment.
  • Ethical Considerations: Address ethical implications, especially for human subjects, ensuring consent or ethics board approval if needed.

Formulating Hypotheses

  • Null Hypothesis: "The content shows no significant signs of being AI-generated."
  • Alternative Hypothesis: "The content shows significant signs of being AI-generated."

Structured Analytical Techniques (SATs), such as Analysis of Competing Hypotheses (ACH) and Key Assumptions Check (KAC), help refine hypotheses. Use the SATs wiki page to guide planning, brainstorming, data collection, and analysis.

Prepare for Research

Operationalizing Variables

  • Identifying Indicators: Decide on themes or patterns to look for in qualitative data and specific metrics for quantitative data.
  • Measurement Scale: Establish if data is nominal, ordinal, interval, or ratio to guide the analysis.

Ensuring Data Quality

  • Pilot Testing: Conduct trial runs to ensure the reliability and validity of data collection methods.
  • Training Data Collectors: Train team members to minimize errors and ensure consistency.
  • Standardizing Data Entry: Create a standardized format for data entry to streamline processing and analysis.

Data Management Plan

  • Data Storage: Establish secure storage solutions accessible for analysis while respecting ethical considerations.
  • Data Processing Procedures: Define how data will be cleaned and prepared for analysis, including how to handle missing data.
  • Version Control: Implement a version control system for datasets to manage updates and collaboration.

Team Collaboration

  • Communication Channels: Set up regular meetings and communication protocols to keep the team informed.
  • Role Definition: Clarify roles and responsibilities in data collection and analysis.
  • Documentation: Maintain detailed records of data collection, issues, and resolutions.

Preparing Systems and Devices for Research

Setting up devices and accounts for research is important for privacy, security, and obtaining unbiased results. Use the following resources to secure your workstation.

Virtual Machine for Research

Virtual Machines or containerization improve security and privacy by isolating the research environment from the host system. See Setting Up a Research Virtual Machine for more details.

Virtual Private Network (VPN) for Research

A VPN can protect privacy while researching and help bypass website geographic restrictions. Check the community VPN guide to choose the right VPN for your research.

Kasm Virtual Environment

Kasm allows you to run a virtual machine in a web browser, useful for research on devices without local resources. Find the self-hosted version of Kasm here.

Pre-Browsing Checks

Run the following checks before browsing to ensure privacy and security:

1. DNS / IP Leak Test - Confirm your location.

2. Cover Your Tracks EFF - Browser canvas check.

3. Browser Cookie Tester

4. InAppBrowser

5. AdBlock Test - Ensure ads are blocked.

See the full Digital Force Protection Guide for more detailed guidance.