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Wikipedia Pageviews: 90-Day Attention Trend for Topics

Daily human pageviews over the last 90 days (total, daily average, peak day and the daily series) for the Wikipedia articles on ChatGPT, Bitcoin and Taylor Swift, with the article summary and URL. For marketers, analysts and researchers measuring public attention to brands, people or topics. Replace the queries, change pageviewsDays, and schedule it to spot spikes.

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Wikipedia Scraper — Search, Summaries & Full Text
Wikipedia Scraper — Search, Summaries & Full Textyadroo/wikipedia-search
Query
Title
Views
Per day
+6 fields
Text
Number
Boolean
List
Object

Input

Search queries or page titles(required):ChatGPT+2
Pageviews window (days):90
Include daily pageview series:true

Output fields

Query
Title
Views
Per day
Peak day
Peak views
From
To
Days
URL

How it works

Sign up on Apify or log in

The Wikipedia Scraper — Search, Summaries & Full Text Actor is ready to run with the inputs already set for "Wikipedia Pageviews: 90-Day Attention Trend for Topics". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Wikipedia Pageviews: 90-Day Attention Trend for Topics" task

The Wikipedia Scraper — Search, Summaries & Full Text Actor will start running based on the input automatically. You can also change all the input fields, like search queries or page titles, pageviews window (days), and more, to match your specific use case.

Receive the "Wikipedia Pageviews: 90-Day Attention Trend for Topics" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as query, title, views, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Wikipedia Pageviews: 90-Day Attention Trend for Topics" task via API.

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