Methodological & Data Review Criteria
- Auditing Digital Data Collection Tools
Submissions to the journal undergo a specialized methodological review to verify the technical integrity and soundness of the software and digital tools utilized to monitor and analyze online content. This includes evaluating social media algorithmic analysis tools, data scraping software, and Social Network Analysis (SNA) frameworks, ensuring the scientific legitimacy and ethical compliance of their deployment.
- Validity of Virtual Populations and Samples
Reviewers are tasked with rigorously evaluating the representativeness of digitally selected samples (such as social media profiles, short-form video content, and digital news platforms). This process ensures that the researcher demonstrates a critical awareness of algorithmic biases and guarantees that the dataset has been systematically filtered to exclude automated accounts (bots) that could skew or distort the empirical findings.
- Integrity of Statistical Analysis and Data Journalism
In quantitative research and big data-driven communication studies, all statistical parameters and indicators are meticulously audited. This evaluation ensures that analytical software (such as SPSS or R) is deployed in strict compliance with its underlying scientific assumptions, and that tables, charts, and data visualizations accurately reflect the empirical results without distortion or arbitrary interpretation.
- Ethics of Digital Audience Observation
This criterion assesses the researcher’s adherence to established ethical standards when investigating user behavior within virtual environments. Key considerations include respecting privacy boundaries inside closed digital groups and forums, maintaining absolute anonymity for human subjects, and safeguarding vulnerable populations—unless the specific nature of the study strictly requires the public tracking of prominent public figures.
