Distorting Allen Ginsberg's intuition of Liverpool in its title, Tate Liverpool will present an exhibition from February to September 2007 to mark the city's 800th anniversary. This accompanying exhibition catalogue investigates how the city has been an influence and inspiration to a wide range of visual artists.

Cited by 0

Timeline

Katherine E. Miller · OSF Preprints (OSF Preprints) · 2021

Cited by 0

Timeline

Pluto Press eBooks · 2022

Cited by 0

Timeline

Pluto Press eBooks · 2017

Cited by 0

Timeline

Amy Nathan, Sarah Keys Evans · 2026

Cited by 0

Timeline

Ayia Gournia, Christopher Mee, Christopher Mee · 2011

Cited by 0Open access

Timeline

it habibi · Mendeley Data · 2026

Google Trends Timeline Dataset The second dataset was directly downloaded from the Google Trends platform using its official export feature. The "Interest Over Time" graph in Google Trends provides a normalized time series of search volume for a given keyword or brand. For each brand, data was exported as a CSV file by selecting the appropriate time range (2014–2024) and region (Iran). This resulted in a continuous timeline of search popularity, used to calculate indicators such as: - Brand Awareness in Google (BAG) - Growth Rate of Awareness in Google (BAGR) The exported file includes timestamps and corresponding interest scores (0–100) normalized by Google. Google Trends Query Design and Cross-series Comparability: Google Trends normalizes each term within the query-specific time window, assigning values on a relative 0–100 scale. To ensure cross-brand comparability and avoid the known issue of inconsistent baselines across separate queries, both brand names (“Irancell” and “Hamrah Aval”) were retrieved together in a single multi-term query. This approach forces Google Trends to apply a shared normalization baseline, ensuring that all series are directly comparable at every point in time. Consequently, BAG, BAGR, and the BPG indicator are derived from time series that reflect genuine differences in public search interest rather than artifacts of independent normalization. We also clarify that this principle applies to the entire EKPI framework: all indicators are designed to be collected simultaneously across competing brands, ensuring that any platform-level fluctuations affect all entities equally and preserving the validity of all comparative measurements.

Cited by 0Open access