anklagelsenshare

Anklagelsenshare is a proposed metric in discourse analysis and digital media research. It measures the share of utterances in a defined dataset that contain an explicit accusation directed at a subject, such as a public figure, organization, or policy. The metric aims to quantify how much accusatory framing appears in discussions and can be used to compare moments in time, platforms, or communities.

Etymology: The term combines the Nordic-root word anklage, meaning accusation, with the English word share. It is used in academic discussions as a descriptive label for a specific type of linguistic signaling in online discourse.

Calculation and methodology: Anklagelsenshare is typically expressed as a percentage: (N_accusation_messages / N_total_messages) × 100. Detection may rely on keyword lists (for example, phrases like "is accused of" or "alleged") or on machine learning classifiers trained to identify explicit accusations and their targets. Researchers define the sampling frame, such as a time window, topic, language, or platform.

Applications: The metric is applied to study political discourse, media accountability, corporate reputation, and social movements. It supports cross-platform comparisons, tracking discourse shifts after events, and evaluating rhetorical strategies used to blame or implicate subjects.

Limitations and criticisms: Challenges include distinguishing explicit accusations from rhetorical questions, sarcasm, or nuanced framing; misclassification due to language variation; and ethical concerns around surveillance and privacy. Cross-language comparability and data access can also affect validity and generalizability.

See also: sentiment analysis, discourse analysis, online misinformation.