Understanding the Index
Our unique methodology combines data-driven insight with empirical analysis to shed light on who holds influence in the European Parliament.
The Burson Influence Index is an objective, and data-driven analysis of the ability of Members of the European Parliament (MEPs) to shape legislation and drive the public debate.
How we measure influence
We measure influence through two key dimensions: Parliamentary Influence and Public Influence, using a robust statistical methodology and validated by principle component analysis (PCA).
Parliamentary Influence
The ability to influence legislation, shape the political agenda, and gain positions of power. Parliamentary influence is evaluated using data points including:
Leadership
Positions of influence regarding group coordination and the parliamentary bureau.
Engagement
General activity and collaboration including networking roles outside plenary meetings.
Legislative Design
The ability to shape a specific piece of legislation, down to detailed levels.
Experience
Seniority in years served in parliament, including formal positions held in previous terms.
Public Influence
The ability to shape the public debate is evaluated across three main categories of influence: social media, news media and search. Public influence is evaluated using data points including:
Social Media Engagement
The reach, relevance, and resonance of the politician's activity on X (formerly Twitter), as well as audience size on LinkedIn and Bluesky.
News Media Visibility
The volume of mentions of the politician in mainstream media.
Public Awareness
The extent to which politicians are searched for on Google.
A statistical procedure called principal component analysis (PCA) is applied to combine these indicators into a single score for parliamentary influence and a single score for public influence. Reducing complexity while retaining a maximum amount of information, PCA is widely used in the creation of indices and is considered to be an objective, data-driven approach to calculating influence scores.