Historical Web Data for Deeper Insights

Tap into over 80TB of historical data from news, blogs, discussions and reviews from across the web for insights at scale.
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Archived Web Data for Big Data Analytics

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Access big historical data from news, blogs, discussions and review sites, dating back to 2008

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Tap into archived web data from around the world, in multiple languages

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Generate bigger insights with rich historical data, instantly accessible through our robust API

Unlock Big Web Data with Historical Data
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Posts Indexed Daily
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Websites
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Years' Historical Data
Access Archived Web Data For

Big Data Analytics

Features1

Advanced Filters

Easily sort historical data by topics, organizations, time frames, and more

Features2

Easy Integration

Instantly access the biggest repository of historical data feeds via API or by running a query yourself

Features3

Pay Per Use

Only pay for the posts you get

Scale Your Data Analytics with

Archived Web Data

LLM training & Machine Learning

Leverage Webz.io’s structured historical datasets to create smarter and powerful automated models

Media Monitoring

Get the fuller picture of a brand with big historical data repositories with data from across any region, in multiple languages

Financial Analysis

Create advanced predictive analytics based on business trends and performance over time with our deep historical data

Risk Intelligence

Monitor critical risk signals from around the world related to supply chain risks, third-party risks, Know Your Customer (KYC) and corporate and travel security

Unleash The Power of

Structured Archived Web Data

Power applications and analytics with historical data in JSON format
See below filtered results in JSON format from the following query:
Query:
site_type:(news OR blogs) is_first:true Netflix ((factual OR documentaries OR documentary OR docuseries OR “true crime” OR “true story” OR “based on real life” OR “based on real events”) OR (drama))

{

entities: {

persons: [

{

name: “squid” ,

sentiment: “positive”

} ,

{

name: “kevin smith” ,

sentiment: “none”

} ,

] ,

locations: [ ] ,

organizations: [

{

name: “netflix” ,

sentiment: “positive”

} ,

{

name: “bridgerton” ,

sentiment: “none”

} ,

]

} ,

updated: “2021-10-13T03:59:54.001+03:00” ,

highlightThreadTitle: “” ,

uuid: “6477567a8b4cfe9c07819ae7999d35a8e7dbc305” ,

thread: {

social: {

gplus: {

shares: 0

} ,

pinterest: {

shares: 0

} ,

vk: {

shares: 0

} ,

linkedin: {

shares: 0

} ,

facebook: {

likes: 611 ,

comments: 101 ,

shares: 26

} ,

stumbledupon: {

shares: 0

}

} ,

reach: {

updated: “2020-10-15T14:25:00.000+03:00” ,

page_views: {

per_user: 2.1 ,

per_million: 5.36

} ,

per_million: 100

} ,

site_full: “www.avclub.com” ,

main_image: “https://i.kinja-img.com/gawker-media/image/upload/c_fill,f_auto,fl_progressive,g_center,h_675,pg_1,q_80,w_1200/672fd005a26c07042bb181e356221437.png” ,

site_section: “http://www.avclub.com/feed/rss/?tags=books” ,

section_title: “The A.V. Club” ,

url: “https://www.avclub.com/surprise-netflix-says-squid-game-is-their-most-success-1847851614” ,

country: “US” ,

domain_rank: 7064 ,

title: “Surprise! Netflix says Squid Game is their most successful series launch to date” ,

performance_score: 0 ,

site: “avclub.com” ,

site_categories: [

“television” ,

“entertainment”

] ,

participants_count: 1 ,

title_full: “Surprise! Netflix says Squid Game is their most successful series launch to date” ,

spam_score: 0 ,

site_type: “blogs” ,

published: “2021-10-13T03:56:00.000+03:00” ,

replies_count: 0 ,

uuid: “6477567a8b4cfe9c07819ae7999d35a8e7dbc305”

} ,

author: “Matt Schimkowitz” ,

url: “https://www.avclub.com/surprise-netflix-says-squid-game-is-their-most-success-1847851614” ,

ord_in_thread: 0 ,

title: “Surprise! Netflix says Squid Game is their most successful series launch to date” ,

external_images: [ ] ,

highlightText: “” ,

language: “english” ,

text: “Netflix loves to call their latest, buzziest show their most successful show of all time . And Squid Game is no different . Earlier today, the company tweeted that 111 million people watched the first season of the hit Korean thriller in its first 28 days of release, crushing the company’s previous record-holder Bridgerton , which pulled in a paltry 82 million viewers. To thank fans, that big, creepy doll from Squid Game announced in a video that all 111 million VIPs made the show number one around the world. And according to Netflix, that’s what happened. By their metrics, Squid Game reached the top of their charts in 90 countries since debuting in September. Of course, it’s worth noting that what Netflix counts as a view is a little askew—to steal a phrase from Kevin Smith. The company’s official “view” means a user watched at least two minutes of any episode. This means that if someone sat around long enough for a video to auto-play on the platform and then let it roll until it reached “Netflix presents,” they more or less counted in the company’s 111 million. It’s also, you know, sketchy to just accept the view counts from Netflix about Netflix without corroboration. So please, take these numbers with a grain of salt. Squid Game would join the ranks of Money Heist , Dark, and Lupin in terms of wildly successful and buzzy non-English language dramas. According to Deadline , the company goes further than its competitors in terms of subtitling and dubbing. In particular, Squid Game is available in more than 30 languages. Nevertheless, the numbers indicate Netflix’s further “internationalization”—not our term—of its offerings. They even earned nods from the company’s former competitor and weirdo billionaire Jeff Bezos, who, as far as we can tell, coined the term “internationalization.” “Reed Hastings and Ted Sarandos and the team at Netflix get it right so often,” Bezos tweeted earlier this month. “Their internationalization strategy isn’t easy, and they’re making it work. Impressive and inspiring. (And I can’t wait to watch the show).” Now we’re left to wonder whether or not Bezos is one of the 111 million VIPs that watched at least two minutes of Squid Game.” ,

external_links: [

“https://deadline.com/2021/10/squid-game-111-million-views-in-first-month-cruising-past-bridgerton-top-all-time-netflix-original-1234854955/” ,

“https://twitter.com/JeffBezos/status/1444431829214248960” ,

“https://www.deadline.com/2021/10/squid-game-111-million-views-in-first-month-cruising-past-bridgerton-top-all-time-netflix-original-1234854955/” ,

“https://twitter.com/JeffBezos/status/1444431829214248960?ref_src=twsrc%5Etfw” ,

“https://deadline.com/2021/10/squid-game-111-million-views-in-first-month-cruising-past-bridgerton-top-all-time-netflix-original-1234854955” ,

“https://www.twitter.com/JeffBezos/status/1444431829214248960?ref_src=twsrc%5Etfw”

] ,

published: “2021-10-13T03:56:00.000+03:00” ,

parent_url: NULL ,

crawled: “2021-10-13T03:59:54.001+03:00” ,

highlightTitle: “” ,

rating: NULL

} ,

 

For more information, check out our Developer Hub which contains helpful DocumentationVideo TutorialsUse Cases and more
Better Analytics

With Big Historical Web Data

Run queries based on people, locations, organizations and topics.

entities: {

persons: [

{

name: “squid” ,

sentiment: “positive”

} ,

{

name: “kevin smith” ,

sentiment: “none”

} ,

] ,

locations: [ ] ,

organizations: [

{

name: “netflix” ,

sentiment: “positive”

} ,

Understand the sentiment of an article with machine learning.

name: “Android” ,

polarity: “strong positive” ,

polarities: {

negative: [ ] ,

strong_negative: [ ] ,

positive: [

2845

] ,

strong_positive: [

844

] ,

neutral: [ ] ,

no_sentiment: [

1620 ,

4686

]

} ,

frequency: 4 ,

relevance: 50

Rank query results by social reach, broken down by engagement and platform.

thread: {

social: {

gplus: {

shares: 12

} ,

pinterest: {

shares: 3

} ,

vk: {

shares: 25

} ,

linkedin: {

shares: 9

} ,

facebook: {

likes: 611 ,

comments: 101 ,

shares: 26

} ,

}

Group similar articles easily, with auto-generated categories.

categories: [

{

level: 3 ,

name: “arts, culture and entertainment – television – soap opera” ,

taxonomy: “IPTC” ,

relative_relevance: 100 ,

absolute_relevance: 0.72848845

} ,

{

level: 1 ,

name: “Home and Garden” ,

taxonomy: “IAB” ,

relative_relevance: 100 ,

absolute_relevance: 1

} ,

]

Get the whole text of every article, post, thread or review included in your results.

anguage: “english” ,

text: “Netflix loves to call their latest, buzziest show their most successful show of all time . And Squid Game is no different . Earlier today, the company tweeted that 111 million people watched the first season of the hit Korean thriller in its first 28 days of release, crushing the company’s previous record-holder Bridgerton , which pulled in a paltry 82 million viewers. To thank fans, that big, creepy doll from Squid Game announced in a video that all 111 million VIPs made the show number one around the world. And according to Netflix, that’s what happened. By their metrics, Squid Game reached the top of their charts in 90 countries since debuting in September. Of course, it’s worth noting that what Netflix counts as a view is a little askew—to steal a phrase from Kevin Smith. The company’s official “view” means a user watched at least two minutes of any episode. This means that if someone sat around long enough for a video to auto-play on the platform and then let it roll until it reached “Netflix presents,” they more or less counted in the company’s 111 million. It’s also, you know, sketchy to just accept the view counts from Netflix about Netflix without corroboration. So please, take these numbers with a grain of salt.” ,

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Have a
Question?
Our historical data includes everything older than 30 days from News, Blogs, Forums and Reviews, going back to January 2008. The data is crawled from a range of different sources, languages and categories; ready-made for predictive analysis, risk modeling, NLP, machine learning and deep sentiment analysis.
It’s simple. First you put in your query, you can also use an old query you ran before. Then you select the time frame and then you let it run. Next, you can get the entire dataset for the time frame you selected.
Yes, you can get the full text of every page going back to 2008.
The price depends on consumption. You only pay for the results you get and not per query. To find out more, set up a call with our data consultant today.
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