konference Social media ve finančních službách

1. Social media a
prediktivní analýza
15. 6. 2011 Josef Šlerka, Praha
konference Social media ve finančních službách

3. Predictive analytics
Predictive analytics encompasses a variety of
statistical techniques from modeling, data mining
and game theory that analyze current and historical
facts to make predictions about future events.
(WIKIPEDIA)

4. Predictive analytics
In business, predictive models exploit patterns
found in historical and transactional data to identify
risks and opportunities. Models capture relationships
among many factors to allow assessment of risk or
potential associated with a particular set of
conditions, guiding decision making for candidate
transactions. (WIKIPEDIA)

5. Search jako signál
Hyunyoung Choi, Hal Varia:
Predicting the Present with Google Trends

7. Jak je to možné?
Život je hledání ... (taky)
a dříve než se rozhodneme, tak hledáme ... (taky)

9. Google Insights
služba, kterou Google postkytuje zadarmo
lze ji využít i pro predikční analýzy
Nikolaos Askitas, Klaus F. Zimmermann:
Google Econometrics and Unemployment
Forecasting

11. Time to Release (Days) Time to Release (Days) Week
Fig. 1. Search volume for the movie Transformers 2 (A) and the video game Tom Clancy’s H.A.W.X. (B) prior to and after their release, and search and Billboard
rank for the song “Right Round” by Flo Rida (C).
A of the song “Right Round” in terms of B
Transformers 2
C
search volume closely H.A.W.X in order to account for the highly skewed distributions of
Tom Clancy's where, Right Round
tracks its rank on the Billboard Hot 100 chart. popularity, both revenue and search volume are log-transformed.
Thus motivated, we now investigate whether search activity is For songs, search data were collected from Yahoo!’s dedicated
a systematic leading indicator of consumer activity by forecasting music site, music.yahoo.com. We predict the weekly Billboard
10
Search Volume (i) opening weekend box-office revenue for 119 feature films re- rank using search rank from the current and previous weeks:
Search Volume
leased in the United States between October 2008 and September
2009; (ii) first-month sales of video games across all gaming 20
Rank
billboardtþ1 ¼ β0 þ β1 searcht þ β2 searcht−1 þ :
platforms (e.g., Xbox, PlayStation, etc.) for 106 games released
between September 2008 and September 2009; and (iii) the 30
weekly rank of 307 songs that appeared on the Billboard Hot Fig. 2 A–C shows that search-based predictions are strongly
100 list between March and September 2009. Search data for mo- correlated with realized outcomes for movies (0.85) and video
Billboard
vies and video games come from Yahoo!’s Web search query logs games (0.76) and moderately correlated for music (0.56), where
40 Search
for the US market. Predictions in these domains are based on in each case revenue or rank is predicted on the day immediately
linear models with Gaussian 20
−30 −20 −10 0 10 error of the form
30 −30 −20 −10 0 preceding the event of interest. Moreover, Fig. 2 D–F shows that
10 20 30 Mar−09 Apr−09 May−09 Jun−09 Jul−09 Aug−09
Time to Release (Days) the predictive power of search persists as far Week several weeks
Time to Release (Days) out as
logðrevenueÞ ¼ β0 þ β1 logðsearchÞ þ ; in advance—for example, four weeks prior to a movie’s release
Fig. 1. Search volume for the movie Transformers 2 (A) and the video game Tom Clancy’s H.A.W.X. (B) prior to and after their release, and search and Billboard
rank for the song “Right Round” by Flo Rida (C).
Movies Video Games Music
A 10 B 10 7
C
100
of the song “Right Round” in terms of search volume closely where, in order to account for the highly skewed distributions of
COMPUTER SCIENCES
10
Actual Revenue (Dollars)
Actual Revenue (Dollars)
tracks its rank on the Billboard Hot 100 chart. 106 popularity, both revenue80 search volume are log-transformed.
and
Actual Billboard Rank
Thus motivated, we now investigate whether search activity is
10
For songs, search data were collected from Yahoo!’s dedicated
a systematic leading indicator of consumer activity by
10 10 5 forecasting 60
music site, music.yahoo.com. We predict the weekly Billboard
(i) opening weekend box-office revenue for 119 feature films re- rank using search rank from the current and previous weeks:
40
leased in the United States between October 2008 and September
10
4
10
2009; (ii) 10first-month sales of video games across all gaming
billboardtþ1 ¼ β20 þ β1 searcht þ β2 searcht−1 þ :
Non−Sequel
platforms (e.g., Xbox, PlayStation, etc.) for 106 games released 0
SOCIAL SCIENCES
Sequel
between September 2008 and September 2009; 10 and (iii) the
3
10 0
weekly rank 10 307 songs that appeared on the Billboard Hot
of 10 10 10 10 10 10
3 4 5 6 7 8 9
10 3
104
10Fig. 210
5
A–C shows that search-based predictions are strongly
6
10 7
0 20 40 60 80 100
Predicted Revenue (Dollars) Predicted Revenue (Dollars) with realized outcomes for movies Rank
correlated Predicted Billboard (0.85) and video
100 list between March and September 2009. Search data for mo-
vies and video games come from Yahoo!’s Web search query logs Games (0.76) and moderately correlated for music (0.56), where
D 0.9 Movies
E 0.9 Video games
F rank Music
for the US market. Predictions in these domains are based on in each case revenue or 0.9 is predicted on the day immediately
linear models with Gaussian error of the form preceding the event of interest. Moreover, Fig. 2 D–F shows that
0.8 0.8
the predictive power of search persists as far out as several weeks
0.8
logðrevenueÞ ¼ β0 þ β1 logðsearchÞ þ ; in advance—for example, four weeks prior to a movie’s release
0.7 0.7
Model Fit
Model Fit
Model Fit
0.7
Movies Video Games Music
A 10 0.6 B 10 7
0.6 C0.6
100
COMPUTER SCIENCES
0.5 0.5 0.5
10
al Revenue (Dollars)
al Revenue (Dollars)
106
tual Billboard Rank
80
10 0.4 0.4 0.4
−6 −5 −4 −3 −2 −1 0 −6 −5 −4 −3 −2 −1 0 −6 −5 −4 −3 −2 −1 0
60
10 Time to Release (Weeks) 105 Time to Release (Weeks) Time to Release (Weeks)
10 Fig. 2. Search-based predictions for box-office movie revenue (A), first-month video game sales (B), and the Billboard rank of songs (C), where predictions are
40
made immediately prior to the event of interest; correlation between predicted and actual outcomes when predictions are based on query data t weeks prior
4

12. Funguje i u nás?
nejsou žadné přesné studie
není důvod, aby nefungoval

15. Social media jako signál
Život NENÍ jen hledání ... Fans, followers, pages
“Co se vám honí hlavou?” (Facebook)
“What’s happening?” (Twitter)

16. Predikce burzy

17. Predikce burzy
To put it in simple words, when the emotions on twitter
fly high, that is when people express a lot of hope, fear,
and worry, the Dow goes down the next day. When
people have less hope, fear, and worry, the Dow goes up.
It therefore seems that just checking on twitter for
emotional outbursts of any kind gives a predictor of how
the stock market will be doing the next day.
Zhang, Fuehres, Peter A. Gloor: Predicting Stock Market Indicators Through Twitter “I hope it is not as bad as I fear”

18. Predikce akcií
sledované akcie Starbucks, Coca Cola a Nike
použité signály Facebook Fans, Twitter flowers,
YouTube Views

20. Predikce voleb
volby do amerického senátu
signálem byl počet followerů na Twitteru
korelace mezi vítězstvím a počtem byla 71%
u porovnání FB fanoušků dokonce 80%

21. Funguje to i u nás?
Zdá, se že ano:-)
Výzkum na datech ze www.ataxosocialinsider.cz

22. Ataxo Social Insider
nástroj pro analýzu dat ze sociálních sítí, diskusních
fór, blogů a zpravodajských serverů

23. Ataxo Social Insider

27. A co predikce?
Case study:
počty zmínek na Facebooku a návštěvnost filmu

28. zmínky o Inception na českém Facebooku 2010 a divácký ohlas

29. Harry Potter na českém Facebooku 2010 a divácký ohlas

30. FB zmínky jako signál
Korelace ukazuje schopnost předvídat dynamiku
tržeb filmů, protože lidé většinou dělají, co říkají....

31. Budoucnost?
Propojme data a dívejme se...

32. Profilování klientů
propojení statusů uživatelů s jejich finačním
chováním
predikce solventnosti
míra spolehlivosti jejich sítě
ověření reality

33. Hledání produktů
šití produktů na míru
objevování patterns v chování

34. Půjde to?
Jde to! V USA firma RapLeaf.
U nás zatím není poptávka.
Data ano.

35. Děkuji za pozornost
josef.slerka@ataxo.com
www.ataxointeractive.com
twitter.com/josefslerka