Psychoinformatics in management

PSYCHOINFORMATICS IN MANAGEMENT
Amrita Vishwa VidyapeethamD E B D U L A L D U T T A R O Y , P H . D . ( P S Y . )
P S Y C H O L O G Y R E S E A R C H U N I T
I N D I A N S T A T I S T I C A L I N S T I T U T E ,
KOLKATA, INDIA
d d r o y @ i s i c a l . a c . i n , d d u t t a r o y @ g m a i l . c o m
V E N U E : V G S O M , I I T . , K G P
D A T E : 1 1 . 0 5 , 2 0 1 5

“We have stepped into the new
millennium with great hopes and
expectations of change. …..The real
change must happen within
ourselves”.
Sri Mata Amritanandamayi Devi

WE L C O M E T O I N D I A N S T A T I S T I C A L
I N S T I T U T E ( I S I ) , A
U N I Q U E I N S T I T U T I O N D E V O T E D T O
T H E R E S E A R C H , T E A C H I N G A N D
A P P L I C A T I O N O F S T A T I S T I C S ,
N A T U R A L S C I E N C E S A N D S O C I A L
S C I E N C E S . F O U N D E D B Y P R O F E S S O R
P . C . M A H A L A N O B I S I N K O L K A T A O N
1 7 T H D E C E M B E R , 1 9 3 1 ,
T H E I N S T I T U T E G A I N E D T H E S T A T U S
O F A N I N S T I T U T I O N O F N A T I O N A L
I M P O R T A N C E B Y A N A C T O F T H E
I N D I A N P A R L I A M E N T I N 1 9 5 9 .
T H E H E A D Q U A R T E R S O F I S I I S
L O C A T E D I N T H E N O R T H E R N F R I N G E
O F T H E M E T R O P O L I S O F K O L K A T A .
A D D I T I O N A L L Y , T H E R E A R E T W O
C E N T R E S L O C A T E D I N D E L H I A N D
B A N G A L O R E .
R E S E A R C H I N S T A T I S T I C S A N D
R E L A T E D D I S C I P L I N E S I S T H E
P R I M A R Y A C T I V I T Y O F T H E
I N S T I T U T E .
T E A C H I N G A C T I V I T I E S A R E
U N D E R T A K E N M A I N L Y I N K O L K A T A ,
D E L H I A N D B A N G A L O R E . O F F I C E S O F
T H E I N S T I T U T E L O C A T E D I N S E V E R A L
O T H E R C I T I E S I N I N D I A A R E
P R I M A R I L Y E N G A G E D I N P R O J E C T S
A N D C O N S U L T A N C Y I N S T A T I S T I C A L
Q U A L I T Y C O N T R O L A N D O P E R A T I O N S
R E S E A R C H ' .
2 5 0 F A C U L T Y M E M B E R S , 1 0 0 0
S U P P O R T I N G S T A F F S ,
INDIAN STATISTICAL INSTITUTE
It has a long and proud tradition of
excellence in training, teaching and research
in a number of academic disciplines
including statistics, mathematics, computer
science, economics, biology, geology,
physics and social science. It attracts some
of the brightest minds from all over India,
and its alumni have made outstanding
contributions to academics, governance and
industry. – Prof. Bimal K Roy, The Director

 SCIENTISTS OF THIS UNIT CONDUCT RESEARCH ON
APPLICATION OF STATISTICS AND MATHEMATICS IN
EXPLAINING DIFFERENT PSYCHOLOGICAL
PHENOMENA AND PSYCHOLOGICAL TEST
DEVELOPMENT THROUGH INTERNAL AND EXTERNAL
FUNDING PROJECTS, SOMETIMES IN COLLABORATION
WITH SCIENTISTS OF OTHER UNITS OF ISI/ OR OTHER
ORGANIZATIONS.
 BESIDES, THE FACULTIES OF THE UNIT ARE INVOLVED
IN TEACHING AND TRAINING ACTIVITIES AND ARE
PROVIDING PH.D. GUIDANCE TO THE RESEARCH
FELLOWS SELECTED THROUGH ALL INDIA
EXAMINATIONS OF THE INSTITUTE.
 SCIENTISTS ARE ALSO PROVIDING SERVICES IN
STATISTICAL OR PSYCHOMETRIC ANALYSIS OF
PSYCHOLOGICAL DATA.
PSYCHOLOGY RESEARCH UNIT

Knowledge has to be improved,
challenged, and increased constantly, or it
vanishes.
-Peter Drucker

"Knowledge is like a river; its nature is to flow. The dharma of
knowledge is to flow to all corners of the world and nourish the
cultures there. We should never stem its flow and thereby turn it
into a stagnant pond. It is said that knowledge is the greatest gift
one can give, for knowledge is imperishable. Even if we light a
thousand lamps from one flame, the lustre of the first lamp never
diminishes. Similar is the greatness of knowledge. Knowledge
does not diminish, no matter how much it is shared. In fact, the
more you give, the more it develops and expands."
-- CHANCELLOR AMMA., Amrita Vishwa Vidyapeetham

Management complexity
 With rapid change in globalization, privatization and
liberalization, system of management moves from
fixed to variable systems, non-virtual to virtual
business, local to transnational, structured to
unstructured and their cross variations.

Knowledge is Non-hypothetical and Randomized change
LOOK, MEDITATE AND FEEL , YOU WILL FIND PATTERN

Non-virtual to Virtual & Structured to Unstructured Knowledge of
Business
U
N
P
R
E
D
I
C
T
B
I
L
I
T
Y Local
State
Internationa
l
Transnation
al
Non-virtual
Virtual
Structured Unstructured

Fixed and Variable systems of Management
Fixed Inputs Fixed Transformation
(Man-machine
interaction)
Fixed Outputs
Variable
Inputs
Variable
Transformation
(Socio-technical
process)
Variable
outputs
Fixed system of Management
Variable system of Management
Feedback

 In Fixed system of management the input, transformation
and output are predetermined and fixed. For example one
jute factory produced goods by using the same
machineries, sources of raw materials, traditional workers
and classical management systems.
 But in variable system of management organization is
giving importance on the feed-back on input,
transformation and output. For e.g. one financial institute
is giving on and off the job training to its employees before
introducing e-marketing business in the organization.

Flow of electronic data and creation of
complexity

Non-virtual to Virtual & Structured to Unstructured Business
U
N
P
R
E
D
I
C
T
B
I
L
I
T
Y Local
State
Internationa
l
Transnation
al
Non-virtual
Virtual
Structured Unstructured

Paradigm Shift in Research
 Hypotheses driven research
 Experimental control : Control of Stimulus, tools, response.
 Survey methods : Control over sample, procedure of data
collection, statistical control.
 Non-hypotheses driven research
 Psychoanalysis : Free floating ideas, Word association.
 Psychoinformatics: Discovery of knowledge by response
pattern recognition based on data mining. Data were retrieved
from data warehouse.

What is Psychoinformatics ?
 Psychoinformatics is exploratory research design to
retrieve randomized data from digitized or non-
digitized data warehouse, to clean and mine the data
by appropriate statistical tools, to classify the data
for pattern formation and finally knowledge is
discovered.
 Data (measured response) + Information> Pattern
formation >discovery of knowledge.

Psychoinformatics is the Non-Hypothesis driven Research
Due to rapid change in information archiving system,
researcher is getting access to the randomized data ware
house.
This is not developed out of researcher’s own intention. For
example, in different blogs and virtual social network,
regularly many messages are posted. Researcher can mine
the data to discover specific variable for research.
It uses computer databases to store, retrieve and assist in
understanding psychological information. Data warehouse,
data retrieving, data mining, pattern recognition and
discovery of knowledge are five basic principles of psycho-
informatics.

Principles of Psychoinformatics
 Data Ware House: It is the reservoir of data. It can be in digitized (e.g
national sample survey records, NCRB report,) and non-Digitized form
(e.g. social network, blogs etc.).
 Data Retrieving: It is the process of selecting valuable data, based on
query in the data base.
 Data Mining: It is an analytic process designed to explore data in
search of consistent patterns and/or systematic relationships between
variables.
 Pattern Recognition: It is the stage where pattern can be recognized by
relating the attributes of the variables. Pattern recognition occurs on
the basis of certain model.
 Knowledge Discovery: New knowledge about relationship among the
variables or the process of analysis is discovered.

PARADIGM SHIFT IN PSYCHOLOGICAL RESEARCH
HYPOTHESES DRIVEN
MODEL
 It encourages knowing
psychology through responses
controlled by the
experimenter or test
constructor.
 Knowing psychology through
predetermined hypotheses
limits our knowledge to pre-
assumed psychological traits.
 This causes serious problem
to gauge all determinants of
individual differences in
behaviour.
NON HYPOTHESES DRIVEN
MODEL
 It encourages knowing
psychology through responses
uncontrolled by the
experimenter or test
constructor.
 Knowing psychology through
response pattern recognition.
Pattern finally reflects specific
psychological traits.
 Psychoinformatics is the non-
hypotheses driven model.

Stages
 Data warehouse: Non-Digitized and Digitized.
 Data retrieval : Using computer resources through
coding.
 Data mining : data classification, association using
psychological measurement or statistical reasoning,
models and tools.
 Pattern recognition : Exploring pattern out of
statistical distribution.
 Discovery of knowledge : Development of theory.

Data warehouse
 It is the reservoir of digitized or non-digitized data.
 Digitized ware house: The Digitized warehouses are social
network groups in virtual world. Yahoo groups, Orkut,
Facebook, message boards, blogs and Youtube are the
Digitized warehouses. In the data warehouse, data are stored
in multiple forms like text, numeric, sound, and pictures.
Google research, Science direct.com, Pubmed, Emerald and
Entrez are the research data warehouse.
 Nondigitized data ware house: Answer sheets of board
examinations, case history records of patients, absenteeism
records of factory workers, foot falls in the shopping malls,
National sample survey records are the data warehouse.
Basic assumption of psycho-informatics is that data warehouse
is formed by randomly generated data.

Digitized data warehouse for Sentiment Analysis
 Facebook generates random data.
 Here is a statement: Mother's day is
coming....confused about the gift....any
idea ? At 9:42 PM
 First response came at 9:51 pm, next
9:52, 9:54, 10:21, P.M., 3:43 am, 7:32
am, 7:34am, 7:36am…contd. This
suggests the statement is able to
generate data speedily.
 If we analyze the content, we will see two
principal components- One is tangible
(cooking food, coffee mug) and another
is intangible (Outing with mother,
spending time with mom).
 The tangible gift is suggested by
unemployed juniors (age ranged from 22
to 25 tears) and intangible is suggested
by employed seniors (30-35 years).

Lecture notes: Psychoinformatics by
D. Dutta Roy, ISI., Kolkata

Digitized Data Retrieval
 Digitized data retrieval:
It is the process of
selecting valuable data
based on query in the
data base.
 There are some cross
data base search engines
like Entrez in the
internet. The address of
Entrez is
‘http://www.ncbi.nlm.ni
h.gov/sites/gquery’.
Names Number of citations
Anxiety disorder 2588781
Depression 235173
Conversion reaction 419
Obsessive compulsive
disorder
3247
Hypochondriasis 962
Somatoform disorder 2456
Schizophrenia 11128
Manic depressive 11382
Paranoid disorder 6593
Autism 14624

Non-Digitized data retrieval
 Using coding process. Later, coding will be entered
into the computer.

Data cleaning is done before and
after data mining.
 Before data mining, cleaning is made to fit the data
according to the assumptions of specific statistical
tools to be used. This includes missing data,
unreliable or faulty data (no response wise
difference), data entry errors, outlier etc.
 After data mining using statistical tools, data are
cleaned when data provide unreliable information or
information that can affect model validity, e.g., items
are removed when it can not be fitted. And rescoring
is done after removing the item.

Data mining
 Data mining: Data mining is an analytic process
designed to explore data in search of consistent
patterns and/or systematic relationships between
variables, and then to validate the findings by
applying the detected patterns to new subsets of data
(Fayyad, Girnistein and Wierse, 2002).
 Classification (involves finding rules that partition a
given data set into disjoint classes) and clustering
(conceptual groups in data on the basis of similarity),
prediction are common models (Andrusiewicz and
Orlowska, 1997).

Pattern formation and Discovery of knowledge
Correspondence map of psychiatric classification and complaints
Input Table (Rows x Columns): 54 x 54 (Burt Table)
Dimension 1; Eigenvalue: .22772 (22.77% of Inertia)
Dimension2;Eigenvalue:.11454(11.45%ofInertia)
ANXCLS:0
ANXCLS:1
SOMATCLS:0
SOMATCLS:1
CONVCLS:0
CONVCLS:1
NEUDEPCL:0
NEUDEPCL:1
OCDCLS:0
OCDCLS:1
HYCHOCLS:0
HYCHOCLS:1
PHOBCLS:0
PHOBCLS:1
SCHIZCLS:0
SCHIZCLS:1
MANICCLS:0
MANICCLS:1
PSYDEPCL:0
PSYDEPCL:1
PDDCLS:0
PDDCLS:1
STRECLS:0
STRECLS:1
SOMATCOM:0
SOMATCOM:1
ANXCMP:0
ANXCMP:1
EMWDLCMP:0
EMWDLCMP:1
CONDOCMP:0
CONDOCMP:1
GUILTCMP:0
GUILTCMP:1
TENSCMP:0
TENSCMP:1
MANCMP:0
MANCMP:1
GRANDCMP:0
GRANDCMP:1
DEPMDCMP:0
DEPMDCMP:1
HOSTCMP:0HOSTCMP:1
SUSPICMP:0
SUSPICMP:1
HALLUCMP:0
HALLUCMP:1
UNTHCCMP:0
UNTHCCMP:1
BLUAFCMP:0
BLUAFCMP:1
EXCITCMP:0
EXCITCMP:1
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

Psychoinformatics in management

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