Website stats and analysis

From our discussions with real-life fact checkers, we realized that gathering the relevant background information about a claim or news story, including all sides of the issue, is a critical initial step in a human fact checker’s job. One goal of the Fake News Challenge is to push the state-of-the-art in assisting human fact checkers, by helping them quickly gather the information they need to mak...

2.42 Rating by Usitestat

fakenewschallenge.org was registered 8 years 4 months ago. It is a domain having .org extension. It is estimated worth of $ 8.95 and have a daily income of around $ 0.15. As no active threats were reported recently, fakenewschallenge.org is SAFE to browse.

Traffic Report

Daily Unique Visitors: Not Applicable
Daily Pageviews: Not Applicable

Estimated Valuation

Income Per Day: $ 0.15
Estimated Worth: $ 8.95

Search Engine Indexes

Google Indexed Pages: Not Applicable
Yahoo Indexed Pages: Not Applicable
Bing Indexed Pages: Not Applicable

Search Engine Backlinks

Google Backlinks: Not Applicable
Bing Backlinks: Not Applicable
Alexa BackLinks: Not Applicable

Safety Information

Google Safe Browsing: No Risk Issues
Siteadvisor Rating: Not Applicable
WOT Trustworthiness: Very Poor
WOT Privacy: Very Poor
WOT Child Safety: Very Poor

Website Ranks & Scores

Alexa Rank: Not Applicable
PageSpeed Score: 89 ON 100
Domain Authority: 45 ON 100
Bounce Rate: Not Applicable
Time On Site: Not Applicable

Web Server Information

Hosted IP Address:

192.30.252.154

Hosted Country:

United States US

Location Latitude:

37.7757

Location Longitude:

-122.395

Traffic Classification

Total Traffic: No Data
Direct Traffic: No Data
Referral Traffic: No Data
Search Traffic: No Data
Social Traffic: No Data
Mail Traffic: No Data
Display Traffic: No Data

Search Engine Results For fakenewschallenge.org

Stance Detection Using Traditional Machine Learning Approaches

- https://www.researchgate.net/publication/327838754_The_Fake_News_Challenge_Stance_Detection_Using_Traditional_Machine_Learning_Approaches

24 Sept 2018 ... The Fake News Challenge: Stance Detection Using Traditional Machine Learning ... organizations like FullFact.org suggests to open col-.


An Efficient Spam SMS Analysis Model based on Multinomial Naïve ...

- https://iopscience.iop.org/article/10.1088/1742-6596/2007/1/012047/meta

Fake News Challenge, "Exploring how artificial intelligence technologies could be leveraged to combat fake ... Available: http://www.fakenewschallenge.org.


A Closer Look at Fake News Detection: A Deep Learning Perspective

- https://dl.acm.org/doi/10.1145/3369114.3369149

26 Oct 2019 ... Using the Fake News Challenge (FNC-1) dataset, we have developed ... Fakenewschallenge.org. http://www.fakenewschallenge.org/, 2019.


Toward Automatic Fake News Classification - Semantic Scholar

- https://pdfs.semanticscholar.org/d52d/d5c2a3b29392c9c6df07d1207d50a61c1304.pdf

4http://www.fakenewschallenge.org/ fake news, its influence and automatic detection. In this section, we try to mention and analyze the important.


Being alone together: developing fake news immunity

- https://www.liverpool.ac.uk/humanities-and-social-sciences/research/coronavirus-research/fake-news-immunity/

Furthermore, AI techniques (such as http://www.fakenewschallenge.org) are currently not accurate enough to replace humans in generalised fact-checking.


Using A.I. to Combat Fake News - Towards Data Science

- https://towardsdatascience.com/using-a-i-to-combat-fake-news-34f5a51907d6

In 2016 a fake news challenge with labeled data was released and the goal of ... fake news challenge competition website: http://www.fakenewschallenge.org/.


Experiments on Detecting Fake News using Machine Learning ...

- https://gvpress.com/journals/IJRIA/vol8_no1/vol8_no1_2020_03.html

[6] http://www.fakenewschallenge.org/ [7] D. Katsaros, G. Stavropoulos, and D. Papakostas, “Which machine learning paradigm for fake news detection?


Fake News: A Definition – Informal Logic - Érudit

- https://www.erudit.org/en/journals/informallogic/1900-v1-n1-informallogic04379/1057034ar/

Fake News Challenge. 2017. URL accessed 30 August 2017: . Google Scholar. Fallis, Don. 2015. What is disinformation?


Stance-In-Depth Deep Neural Approach to Stance Classification

- https://www.sciencedirect.com/science/article/pii/S1877050918308640

Fake news challenge website. [Online]. Available: https://fakenewschallenge.org. Google Scholar. 9. J. Chung, C. Gulçehre, K ...


Delip Rao - Founder/Researcher - Page Street Labs | LinkedIn

- https://www.linkedin.com/in/deliprao

Founder of The Fake News Challenge, a non-profit initiative to bring more than 1000 hackers and AI researchers worldwide to ... http://fakenewschallenge.org.


Fake News Challenge

- http://www.fakenewschallenge.org/

For this stage of the challenge, we require all teams to use only the labeled data supplied by FakeNewsChallenge.org (i.e. no external data augmentation is ...


Fake News Detection using Deep Nerual Networks - GitHub Pages

- https://anirudh42.github.io/Fake-News-Detection/

Fake News Detection using Deep Nerual Networks. This project is part of a challenge which can be found at http://www.fakenewschallenge.org/ ...


COVID-19: Being alone together: developing fake news immunity

- https://www.sonar-global.eu/covid-19-projects/covid-19-being-alone-together-developing-fake-news-immunity/

Furthermore, AI techniques (http://www.fakenewschallenge.org) are currently not accurate enough to replace humans in generalised fact-checking.


Ranking-based Method for News Stance Detection - KAUST ...

- https://repository.kaust.edu.sa/bitstream/handle/10754/627607/p41-zhang.pdf?sequence=1

27 Apr 2018 ... initiated the Fake News Challenge (FNC) 1 and the first stage of. FNC (FNC-1) aimed to accelerate ... 1http://www.fakenewschallenge.org/.


A Deep Transfer Learning Approach for Fake News Detection

- http://vigir.missouri.edu/~gdesouza/Research/Conference_CDs/IEEE_WCCI_2020/IJCNN/Papers/N-21846.pdf

namely Fake News Challenge (FNC) dataset (released in Fake ... 1http://www.fakenewschallenge.org/. 978-1-7281-6926-2/20/$31.00 ©2020 IEEE ...


Thinking Thursday Fake News Challenge Activity (ages 7-11) - Twinkl

- https://www.twinkl.co.uk/resource/thinking-thursday-fake-news-challenge-activity-ages-7-11-t-wn-1330

How can I help my child spot fake news? Use this Thinking Thursday Fake News Challenge Activity (ages 7-11) to develop your child's skills at spotting fake ...


Fake Bananas: Detecting Fake News at HackMIT on Paperspace

- https://blog.paperspace.com/fake-news-detection/

2 2 Cisco-Talos' work on the Fake News Challenge ... 4 4 Our training data came from the FakeNewsChallenge.org where in 2016 teams competed to develop ...


Combatting Fake News - GMA

- https://www.gmal.co.uk/combatting-fake-news/

13 Feb 2020 ... Also, initiatives like the Fake News Challenge (http://www.fakenewschallenge.org/) seeks to explore how AI technologies, ...


Fake news challenge - Richard Godden

- https://www.richardgodden.com/aml-fnc/

The Fake news challenge[1] was established to explore how machine learning and AI ... www.fakenewschallenge.org/ GitHub github.com/FakeNewsChallenge.


How it works - Fact Benchmark

- http://factbenchmark.org/how/

... claimbuster, fakenewschallenge.org and the many others who have been working on the problem of creating research and benchmark data sets - many of whom ...


A simple but tough-to-beat baseline for the Fake News Challenge ...

- https://deepai.org/publication/a-simple-but-tough-to-beat-baseline-for-the-fake-news-challenge-stance-detection-task

A simple but tough-to-beat baseline for the Fake News Challenge stance detection task. 07/11/2017 ∙ by Benjamin Riedel, et al. ... fakenewschallenge.org.


Talos Targets Disinformation with Fake News Challenge Victory

- https://blog.talosintelligence.com/2017/06/talos-fake-news-challenge.html

20 Jun 2017 ... Using advanced machine learning and artificial intelligence technology, Talos researchers set their sights on this different kind of cyber- ...

Page Resources Breakdown

Homepage Links Analysis

Website Inpage Analysis

H1 Headings: 6 H2 Headings: 3
H3 Headings: 17 H4 Headings: 36
H5 Headings: 3 H6 Headings: 6
Total IFRAMEs: Not Applicable Total Images: 13
Google Adsense: Not Applicable Google Analytics: UA-91312779-1

Two Phrase Analysis

Words Occurrences Density Possible Spam
fake news 21 0.668 % No
of the 21 0.668 % No
Fake News 13 0.413 % No
on the 13 0.413 % No
in the 12 0.382 % No
Stance Detection 11 0.35 % No
body text 11 0.35 % No
human fact 10 0.318 % No
News Challenge 10 0.318 % No
fact checkers 10 0.318 % No
to the 9 0.286 % No
stance detection 7 0.223 % No
to be 7 0.223 % No
with the 6 0.191 % No
the test 6 0.191 % No
of fake 6 0.191 % No
the claim 6 0.191 % No
the Fake 6 0.191 % No
the headline 6 0.191 % No
will be 6 0.191 % No

Four Phrase Analysis

Words Occurrences Density Possible Spam
the Fake News Challenge 6 0.191 % No
…”      Correct classification 4 0.127 % No
of the Fake News 4 0.127 % No
the fake news problem 3 0.095 % No
headline and body text 3 0.095 % No
Fake News Challenge is 3 0.095 % No
agrees disagrees or discusses 3 0.095 % No
could serve as a 3 0.095 % No
the stance detection task 3 0.095 % No
often for a secondary 2 0.064 % No
Pairs of headline and 2 0.064 % No
of headline and body 2 0.064 % No
goal of the Fake 2 0.064 % No
The data that does 2 0.064 % No
data that does exist 2 0.064 % No
Set Pairs of headline 2 0.064 % No
News Challenge is to 2 0.064 % No
in the test set 2 0.064 % No
incremented by 025 if 2 0.064 % No
by 025 if it 2 0.064 % No

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HTTP Header Analysis

Http-Version: 1.1
Status-Code: 200
Status: 200 OK
Server: GitHub.com
Date: Fri, 01 Oct 2021 03:12:10 GMT
Content-Type: text/html; charset=utf-8
Transfer-Encoding: chunked
x-origin-cache: HIT
Last-Modified: Thu, 15 Jun 2017 20:20:43 GMT
Vary: Accept-Encoding
Access-Control-Allow-Origin: *
ETag: W/"5942ec1b-ce54"
expires: Fri, 01 Oct 2021 03:22:10 GMT
Cache-Control: max-age=600
Content-Encoding: gzip
x-proxy-cache: MISS
X-GitHub-Request-Id: D2DA:0A81:6EE209:A52DEB:61567C8A

Domain Information

Domain Registrar: Public Interest Registry
Registration Date: 2016-12-05 8 years 4 months 3 weeks ago

Domain Nameserver Information

Host IP Address Country
ns-cloud-d1.googledomains.com 216.239.32.109 United States United States
ns-cloud-d2.googledomains.com 216.239.34.109 United States United States
ns-cloud-d3.googledomains.com 216.239.36.109 United States United States
ns-cloud-d4.googledomains.com 216.239.38.109 United States United States

DNS Record Analysis

Host Type TTL Extra
fakenewschallenge.org A 3593 IP: 192.30.252.154
fakenewschallenge.org A 3593 IP: 192.30.252.153
fakenewschallenge.org NS 21600 Target: ns-cloud-d2.googledomains.com
fakenewschallenge.org NS 21600 Target: ns-cloud-d1.googledomains.com
fakenewschallenge.org NS 21600 Target: ns-cloud-d4.googledomains.com
fakenewschallenge.org NS 21600 Target: ns-cloud-d3.googledomains.com
fakenewschallenge.org SOA 21600 MNAME: ns-cloud-d1.googledomains.com
RNAME: cloud-dns-hostmaster.google.com
Serial: 12
Refresh: 21600
Retry: 3600
Expire: 259200
fakenewschallenge.org MX 3600 Priority: 30
Target: alt3.gmr-smtp-in.l.google.com
fakenewschallenge.org MX 3600 Priority: 20
Target: alt2.gmr-smtp-in.l.google.com
fakenewschallenge.org MX 3600 Priority: 10
Target: alt1.gmr-smtp-in.l.google.com
fakenewschallenge.org MX 3600 Priority: 40
Target: alt4.gmr-smtp-in.l.google.com
fakenewschallenge.org MX 3600 Priority: 5
Target: gmr-smtp-in.l.google.com

Full WHOIS Lookup

Domain Name: FAKENEWSCHALLENGE.ORG
Registry Domain ID:
D402200000000868966-LROR
Registrar WHOIS Server:
whois.google.com
Registrar URL:
https://domains.google.com
Updated Date:
2020-12-05T15:00:51Z
Creation Date:
2016-12-05T07:51:01Z
Registry Expiry Date:
2021-12-05T07:51:01Z
Registrar Registration Expiration
Date:
Registrar: Google LLC
Registrar IANA ID:
895
Registrar Abuse Contact Email:
[email protected]
Registrar Abuse Contact Phone:
+1.8772376466
Reseller:
Domain Status: ok
https://icann.org/epp#ok
Registrant Organization: Contact Privacy
Inc. Customer 124957913
Registrant State/Province:
ON
Registrant Country: CA
Name Server:
NS-CLOUD-D1.GOOGLEDOMAINS.COM
Name Server:
NS-CLOUD-D2.GOOGLEDOMAINS.COM
Name Server:
NS-CLOUD-D3.GOOGLEDOMAINS.COM
Name Server:
NS-CLOUD-D4.GOOGLEDOMAINS.COM
DNSSEC: unsigned
URL of the
ICANN Whois Inaccuracy Complaint Form
https://www.icann.org/wicf/)
>>> Last update of WHOIS database:
2021-10-01T03:11:17Z

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