A Praxis of Influence: Framing the Observation and Measurement of Information Power

TL;DR

This paper develops an integrated framework combining politics, computing, and psychology to observe, measure, and analyze the influence of information in international relations and digital platforms, emphasizing impact beyond traditional metrics.

Contribution

It introduces a triadic analytical framework, mapping tactics to objectives and targets, and presents a McCumber-style cube for comprehensive influence analysis, advancing measurement methods.

Findings

Virality and denial of logic exploit fast cognition.

Conventional reach metrics understate impact.

Instrumentation should focus on belief change and decision effects.

Abstract

Information power is the capacity to convert data flows into durable shifts in attention, belief, and behavior. We argue that this power has migrated from broadcast persuasion to platform-ized, data-driven operations that fuse computational delivery with cognitive effects. In this context, we define and bound information power within international relations and the information environment while demonstrating why observing and measuring it demands an integrated lens that combines politics (goals and governance), computing (data movement and algorithmic delivery), and psychology (attention, affect, memory, and belief). The article contributes three elements: (1) a triadic analytical framework that specifies the minimum variables and instrumentation needed for study; (2) two crosswalks that map common objectives (persuade, disrupt, shape) and target classes (leaders, elites, publics) to political, computational, and psychological tactics, yielding practical coding heuristics and testable hypotheses; and (3) a McCumber-style cube for information influence that integrates targets, operations, as well as machines (automation and AI) into a single space. The space provides for comparative analysis, data fusion, and effect measurement. Using recent cases across state and commercial platforms, we illustrate how virality, stickiness, and denial of logic exploit fast cognition, why conventional reach metrics understate impact, and where instrumentation should focus. We conclude with a mixed-methods research program coupling computational sensing including large-language-model text mining with experiments and polling. The intention is to move from detecting activity to estimating belief change and decision effects.