Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Jan Stępień - Tracking those who Track
Search
Munich DataGeeks
July 02, 2013
Technology
1
200
Jan Stępień - Tracking those who Track
Talk by Jan Stępień at the firsta Munich DataGeeks Meetup
Data: 02.07.2013
Munich DataGeeks
July 02, 2013
Tweet
Share
More Decks by Munich DataGeeks
See All by Munich DataGeeks
Florian Haselbeck- Advancing Synthetic Protein Design with Large Language Models
munichdatageeks
0
77
Tobias Ladner- Formal Verification of Neural Networks in Safety-Critical Environments
munichdatageeks
0
97
Uladzislau Sazanovich - JetBrains AI: Deep Dive
munichdatageeks
0
82
Jan Hauffa - A Case Study on Retrieval-Augmented Generation for Document Q&A: Experiences and Future Perspectives
munichdatageeks
0
100
Thomas Schmidt - Revolutionizing SQL Data Model Testing: Introducing SQL-Mock by DeepL
munichdatageeks
0
60
Maximilian Duesberg - The Data is Clear - But Humans are not
munichdatageeks
0
100
Dr.Christoph Mittendorf-Beyond Bard and Transformers: Unconventional ML Use Cases
munichdatageeks
0
150
Heidi Seibold - Are (data) scientists bad at science?
munichdatageeks
0
140
Roland Rodde- Vegetation management for powerlines with remote sensing data
munichdatageeks
0
160
Other Decks in Technology
See All in Technology
united airlines ™®️ USA Contact Numbers: Complete 2025 Support Guide
flyunitedhelp
1
340
KubeCon + CloudNativeCon Japan 2025 Recap
ren510dev
1
380
Glacierだからってコストあきらめてない? / JAWS Meet Glacier Cost
taishin
1
160
Tokyo_reInforce_2025_recap_iam_access_analyzer
hiashisan
0
190
Zero Data Loss Autonomous Recovery Service サービス概要
oracle4engineer
PRO
2
7.8k
Lakebaseを使ったAIエージェントを実装してみる
kameitomohiro
0
130
freeeのアクセシビリティの現在地 / freee's Current Position on Accessibility
ymrl
2
200
Yahoo!しごとカタログ 新しい境地を創るエンジニア募集!
lycorptech_jp
PRO
0
110
SEQUENCE object comparison - db tech showcase 2025 LT2
nori_shinoda
0
140
整頓のジレンマとの戦い〜Tidy First?で振り返る事業とキャリアの歩み〜/Fighting the tidiness dilemma〜Business and Career Milestones Reflected on in Tidy First?〜
bitkey
2
16k
United Airlines Customer Service– Call 1-833-341-3142 Now!
airhelp
0
170
DBのスキルで生き残る技術 - AI時代におけるテーブル設計の勘所
soudai
PRO
50
20k
Featured
See All Featured
Six Lessons from altMBA
skipperchong
28
3.9k
Fantastic passwords and where to find them - at NoRuKo
philnash
51
3.3k
Product Roadmaps are Hard
iamctodd
PRO
54
11k
[RailsConf 2023] Rails as a piece of cake
palkan
55
5.7k
Principles of Awesome APIs and How to Build Them.
keavy
126
17k
Learning to Love Humans: Emotional Interface Design
aarron
273
40k
Building a Modern Day E-commerce SEO Strategy
aleyda
42
7.4k
Automating Front-end Workflow
addyosmani
1370
200k
The Cult of Friendly URLs
andyhume
79
6.5k
The Art of Programming - Codeland 2020
erikaheidi
54
13k
The Web Performance Landscape in 2024 [PerfNow 2024]
tammyeverts
8
690
Docker and Python
trallard
44
3.5k
Transcript
Tracking those who track us Jan Stępień
My name is Jan Stępień and I come from Warsaw
Data analysis is not just big data
Data analysis is fun
It all started with ads tracking “like” buttons other irrelevant
things
1. Use an adblock plugin 2. Block all network communication
to unwelcome domains
My machine website.com ads.website.com
My machine website.com ads.website.com
Let’s capture all those requests!
03.2012 – 06.2013 106 414 requests 322 distinct days approx.
330 requests per day
SQLite3 + Incanter + R + Weka
http_if_none_match http_referer http_accept_encoding http_accept http_cookie http_connection http_host http_user_agent http_version path_info
http_accept_charset http_accept_language http_cache_control http_if_modified_since request_method request_path request_uri query_string remote_host remote_addr script_name server_name server_port server_protocol http_dnt timestamp
timestamp
03 04 05 06 07 08 09 10 11 12
01 02 03 04 05 06 15k 10k 5k 0
00 01 02 03 04 05 06 07 08 09
10 11 12 13 14 15 16 17 18 19 20 21 22 23 100 0 200 300 400 500
8k 6k 4k 2k 0 Mo Tu We Th Fr
Sa Su
http_host
www.google-analytics.com 36197 static.adzerk.net 13983 edge.quantserve.com 11659 www.facebook.com 9641 ad.doubleclick.net 3822
pagead2.googlesyndication.com 3764 s.youtube.com 2173 b.scorecardresearch.com 1974 pubads.g.doubleclick.net 1465 googleads.g.doubleclick.net 1231
48.9% of requests sent to domains owned by Google
http_referer
22902 distinct referrers 4692 distinct domains
Let’s try to combine this dataset with something else
Weather influence?
ogimet.com Humidity, min/max/avg temperature, cloud coverage, visibility, rain/snow, wind speed/direction,
etc.
No correlations!
Tags at stackoverflow.com
http://stackoverflow.com/questions/123/title
data.stackexchange.com
Thanks, wordle.net!
Can be my WWW traffic grouped into clusters?
1. Group requests into 15 minute intervals 2. Count domains
per interval
5008 intervals Each described by over 4500 values
1. Select request from popular domains 2. Group requests into
15 minute intervals 3. Count domains per interval
5008 intervals Each described by 95 values Only 2% of
cells with non-zero values
Principal Component Analysis 95 domains → 16 descriptors
X-means K-means based clustering algorithm
cluster 0 1268 cluster 1 702 cluster 2 651 cluster
3 2387 What is the meaning behind these clusters?
3 stackoverflow.com
2 reddit.com redditmedia.com bbc.co.uk
1 linkedin.com dictionary.reference.com meetup.com
0 rubyonrails.pl developer.android.com tex.stackexchange.com amazon.com youtube.com
How accurate is this clustering? Let’s build a classifier on
the original data
0 1 2 3 ← classified as 1188 29 11
40 cluster 0 47 654 1 0 cluster 1 10 1 622 18 cluster 2 50 0 18 2319 cluster 3 cluster 0: rubyonrails.pl developer.android.com amazon.com youtube.com cluster 1: linkedin.com dictionary.reference.com meetup.com cluster 2: reddit.com redditmedia.com bbc.co.uk cluster 3: stackoverflow.com
Let’s wrap up
Data analysis is not just big data
Data analysis is fun
Thank you very much The picture of Warsaw is ©
Dennis Jarvis 2009