Download study results as an Excel file. Here's what you will find in this file

The Result Assessment Tool allows for automatically scraping search results from search engines, classifying them with existing classifiers and having them assessed by human jurors. In the assessments, the study participants answer questions about the respective search result (e.g. whether the search result is relevant to the query).

When you download your data from RAT, the system generates a comprehensive Excel file. The structure and the variables in that file, which are described in the tables below, provide a detailed overview of the data. You can also RAT sample output showing how the output looks like.

The following table lists all possible variables in a RAT Dataset. The table is divided into four sections:

Main data (this is what is generated in all cases, regardless of which classifiers or assessments you use)
Source data (saved HTML source code and a screenshot of the search result)
Evaluation data (data generated by participants when answering questions about a particular search result)
Classification data (data generated with the help of a classifier, i.e., the SEO classifier)

Main data

Variable	Description	Type
id	Unique identifier for each row in the table	number
query	Keywords of the query.	text
url	URL of the search result.	text
main	Main URL of the search result (e.g. google.com instead of google.com/imghp?hl=en).	text
search engine	Name of the Search Engine	text
position	Rank position of the search result at the time of scraping.	number
title	Title of the search result on the search engine result page, given by the search engine.	text
description	Description of the search result on the search engine result page, given by the search engine.	text
ip	The IP address of the search result.	text
timestamp	The timestamp of scraping.	timestamp

Source data

Variable	Description	Type
html	HTML source code	text
screenshot	Screenshot from the search result	byte
screenshot_timestamp	The timestamp of the screenshot	timestamp

Evaluation data

Variable	Description	Type
participant	Unique identifier for the study participant	number
id_question	Unique identifier for the question asked	text
question	Text of the question	text
value	Answer of the participant to the question.	text
question_timestamp	The timestamp of the answer	timestamp

Classification data

Please note that the table describes the output of the SEO classifier. Other classifiers will output different fields; see the documentation.

seo_class	Result of classifying the probability of applying search engine optimization methods to the search result. (not optimized; probably not optimized; probably optimized; most probably optimized)	text
seo_timestamp	The timestamp of classification of SEO probability of the search result.	timestamp
ads	Matches the domain to a list of websites that use ad services. (1 = match; 0 = no match).	number
canonical	Check whether canonical links were found in the source code of the search result.	number
company	Matching the domain with a list of known companies. Check if the domain could be found.	number
description	Check if a description was found in the source code.	number
external	Counter of external links in a document.	number
h1	Counter of h1 headings in a document.	number
https	Check if the website uses https.	number
internal	Counter of internal links in a document.	number
keyword_density	Calculate the keyword density in a document.	number
keywords_in_source	Counter of keywords found in the source code.	number
keywords_in_url	Counter of keywords in the URL.	number
	Calculated loading time of a web page in seconds.	number
loading_time	Calculated loading time of a web page in seconds.	number
micros	Check whether microdata formats like JSON-LD are used in a document.	number
news	Matching the domain with a list of known news services. Check if the domain could be found.	number
nofollow	Counter of nofollow links in a document.	text
not_optimized	Matching the domain with a list of known non SEO optimized documents.	number
	counter of elements in a document with an og: tag.
og	counter of elements in a document with an og: tag.	number
robots_txt	Check if any references to SEO were found in the robots.txt file of a domain.	number
search_engine_services	Matching the domain with a list of known search engine services like books.google.com.	number
shops	Matching of the domain with a list of known shops.	number
	Check whether a sitemap was used on the search results web page.
sitemap		number
title	Check whether a title was used on the search result web page.	number
	List of identified ad services found on the web page.
tools ads	List of identified ad services found on the web page.	list
tools analytics	List of identified analytics services found on the web page.	list
	List of identified caching plugins found on the web page.
tools caching	List of identified caching plugins found on the web page.	list
tools content	List of identified content services found on the web page.	list
tools seo	List of identified SEO plugins found on the web page.	list
tools social	List of identified social plugins found on the web page.	list
url_length	Length of the URL.	number
viewport	Check if a viewport tag was found in the document	number
wordpress	Check, if WordPress is used as CMS	number

Further information about the implementation of the SEO classifier is available at https://osf.io/u8d62.

Contact information for questions about the data set: sebastian.suenkler@haw-hamburg.de.