Applying the principles of behavioral economics to predict behavioral intelligence from the Social Voice of London traffic on twitter

1. London Traffic
Through the Lens of Behavioral
Economics
Sankar Nagarajan
TEXTIENT Analytics
@Twitter
A Sample Study

2. People are sharing their experience
and responding on Twitter to
London’s Traffic conditions …
London Traffic

3. What do we know, rather understand about
people’s experience from the moments of
truth?(traffic) What are the human needs,
motivations, beliefs and goals that can be related?
What can be the Social implications?
BUT

4. Wanted: royal chauffeur who can
deal with London traffic
Source : The Times 19-Feb-2015
URL Link:
http://www.thetimes.co.uk/tto/news/uk/royalfamily/article4359804.ece
State of Affairs !

5. Principles based on
Behavioural Economics can provide ‘Traffic Insights’ from Social Voice
Traffic events and related people’s experience can evoke
different human emotions . Influence of People’s behaviour
may be significantly impacted due to emotions than by
rational thinking. Organizations can leverage this for better
management.
BEHAVIORAL ECONOMICS IS AN EMERGING AREA OF MANAGEMENT

6. Dataset for Predictive Analytics
• Twitter raw data (tweets)
• Twitter search term ‘london traffic’
Uncovering the Behavioral Intelligence
Sampled twice

7. Behavioral Prediction
- People’s feelings
London Traffic

8. Pain/ Suffering
Cognition: Isolation
Behavior: Cry for Help
e.g. The traffic in South East
London is absolute filth.
I'm so stressed I could cry
😐😤😭😔
Dislike / Hate
Cognition: undesirable
Behavior: Get away
Leads to Paranoid State
Leads to Depressive State
Dominant Feelings Predicted : Disgust (Dislike, Hate, Frustration)

9. 1. Dominant emotion of disgust felt as dislike, frustrations and hate
suggests the prevalence of an undesirable, negative traffic scenario
that may trigger behaviours to get away or rid of the situations.
2.Elevated (Disgust + Sadness) suggests feelings of remorse /shame .
The intensity of this negative feeling can be in direct proportion to
how interested people would be to drive in free traffic.
This feeling is about the stopping of the stimulus of an ongoing
positive affect (traffic free driving, smooth traffic) that people did
not want it to stop. This is a crucial information for one to evaluate.
This ‘Shame affect’ provides the motivating information for the
uncovering and removal of impediments(traffic problems) to things
people enjoy (problem free traffic) !
The Affective Psychology of
Disgust, Sadness & Shame
What does the Emotions/ Feelings indicate?

10. Prediction Theme : What’s behind Negative feelings ?
Dominance
Love /Affiliation
Submission
power
love
Affective Influence graph
of Socio-Emotional Shell
Motivational base : People seek to avoid or withdraw from
• Sample Prediction
Low Influence activation : Loss of Power, Care and Autonomy
Sample messages [related]:
SB Highbury backed up from Hamilton to Brydges.
Delays between Dundas and Oxford easing.
SB Highbury still backed up from Dundas to Oxford
due to earlier crash at Dundas.
CR tells us there's a vehicle flipped over on NB
Richmond, north of University
Hate/Hostility
Shame
pride
Joy
Anger
Guilt
Low
Influence
Sadness
Fear
power

11. Predicted Context of the Feelings (What is it related to?)

12. Behavioral Prediction
- People’s Wants
London Traffic

13. Prediction People’s ‘Wants’
Sample Prediction
76%
66%
34%
46%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Higher level of
connect/
relationship
Inquisitiveness Need for Escape Order & Control
Higher level of ‘connect’ is suggestive of wants to lower the
emotional fears and increasing the trust including getting
things under control and not getting nasty surprises in the
traffic scenario.
Inquisitiveness suggestive of mental needs to “know what’s
going on”, Higher levels may indicate lower awareness.
Order & Control: Suggestive of the need to streamline traffic
issues.
Need for Escape: Suggestive of desire to get out of the
situation. Higher levels may indicate a major block / issue
Note: The indicated prediction above is only for the dominant feelings of ‘Disgust’ illustrated
here as a representative specimen. It can be predicted for other feelings such as Fear..
Wants from the traffic experiences

14. Behavioral Prediction
- Motivations
London Traffic

15. Prediction People’s Confidence Vs Caution
Sample Prediction
33 %
49 %
Confidence
Caution
Emotional Loading & Motivation
33: 49 is Ok. But a little unbalanced. A higher unbalance either side
may imply negative characteristics .
For instance too much ‘Caution’ with low ‘Confidence’ may suggest
loss of stability, Uncertainty etc that may require a closer attention.
Note: The indicated prediction above is only for the dominant feelings of ‘Disgust’ illustrated here as a representative
specimen. It can be predicted for other feelings such as Fear..
Cautious treading of the traffic problems Vs
Confidence in its removal or overcoming

16. Prediction Motivations to avoid negative consequences
Sample Prediction
49%
48%81%
40%
People(Disgust)
people(Fear)
People(Angry)
Caution
22%
15%
71%
24%
People(Disgust) people(Fear)
People(Angry) People(Sadness)
Risk Avoidance
9%
37%
12%
13%
People(Disgust) people(Fear)
People(Angry) People(Sadness)
Stupidity Avoidance
 Evaluation: A Higher % feel disgusted (slide#6) due which they might exhibit withdrawal symptoms
(i.e. seek exit from the environment). Referring to the above predicted level of their wants, the
tendencies to avoid negative consequences may be improved. For instance,
Should We reduce the negative bias of traffic related messages through broadcast /social media?
Can Agencies guide travellers better through traffic broadcast? What could lower perceived risks (e.g.
texting while driving?)

17. Behavioral Prediction
- Goals & Beliefs
London Traffic

18. Prediction People’s Goals / Beliefs
Sample Prediction
93%
22%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Freedom/Independence Order/Discipline
Higher level of ‘Freedom/ Independence’ is suggestive of
beliefs and goals to attain a change of situation that would
relieve anxieties (freedom from traffic congestion?). Also
indicates beliefs that promotes coping with the situation.
Lower levels of Social order is suggestive of impulses to
bypass or break orders and rules say in behaviour such as
driving. There is a lower sense of social focus and harmony in
the play.
Note: The indicated prediction above is only for the dominant feelings of ‘Disgust’ illustrated
here as a representative specimen. It can be predicted for other feelings such as Fear..
Actions in pursuit of goals have practical, psychological and social consequences. Goals
& beliefs underlies attitudes in the given scenario.

19. Why Behavioural Insights?
• In a city like London, there are people with varied background across cultures.
• The * Science of economic judgement and choice is highly influenced by Human
Behavioural aspects. (Psychology, Emotions)
• People’s experience and perceptions drives their behaviour and actions. To understand
them, there is a need for ‘Humanized’ insights that may help Governments/Agencies in
this case to connect better with citizens or implement policies to improve systems.
• Most of the intelligence today are transactional that won’t help truly understand people in the digital
landscape.
* Prof. Daniel Kahneman, Princeton University

20. Possible Application areas..?
Intelligent Traffic Aids Risk Management
City Governance
Citizen Safety/
Well being

21. Would be great to get your feedback
Email: sankar[at]textient.com
Thoughts ?
This is just the tip of the iceberg !

22. Digital data hose from
varied touch-points
Your Private digital
consumer text data
Behavioral Intelligence
From Big data
* Affect, Psychology, Cognitive
TEXTIENT
Platform
Analysis
Data Science
Cloud
computing
Analytics
/Report
TEXTIENT Analytics
Instagram
OR
Monitoring
& Analytics
Feeds Historical
This study was enabled by

23. The Next revolution will be Psychological, NOT
Technological !
@rorysutherland
YouTube link
http://bit.ly/15T8TCa
Inspiration

24. THANK YOU!
Twitter @_textient
www.textient.com

25. Behavioral economics helps study the effects
of psychological, social, cognitive, and emotional
factors on the economic decisions of individuals
and institutions and the consequences for market
prices, returns, and the resource allocation.
Source – Wikipedia
http://bit.ly/1gnKPqr
Behavioral Economics 101

26. USING THIS DOCUMENT
Essential Reading
This document is intended to support practitioners’ level of awareness in the context of identifying and leveraging predictive
indictors or cues from Behavioral Economics in the area of Business Intelligence & Analytics.
It’s Intended to provide and enhance business practitioners “knowledge” of factors that are theoretically linked to Behavioral
Economics.
It doesn’t provide a actuarial measure of an individual or a organisations’ behavior, performance or risks
It is not to be used to determine or construct specific notions or legal charges against any individual or an organisation.
It is not to be used as a surveillance tool.

27. The views mentioned in this presentation my /our own.
Data if used, in the document have been sourced from available information in the public
domain and has not been authenticated by any statutory authority.
Although every reasonable effort is made to present current or appropriate information, there
are no guarantees of any kind. Data accuracy cannot be guaranteed. All analysis included
herein are based on data from public sources, but no representation or warranty, expressed or
implied, is made as to their accuracy, completeness, timeliness, or correctness. I am not liable
for any errors or inaccuracies, regardless of cause to you (readers, users).
Disclaimer