+ All Categories
Home > Data & Analytics > Approaches to indiv and societal wellbeing

Approaches to indiv and societal wellbeing

Date post: 23-Jan-2018
Category:
Upload: krista-lagus
View: 207 times
Download: 1 times
Share this document with a friend
20
Approaches to Promote Individual and Societal Wellbeing Krista Lagus [email protected] Artificial Intelligence and Machine Learning for People 2.11.2015
Transcript

Approaches to Promote Individual and Societal

Wellbeing Krista Lagus

[email protected]

Artificial Intelligence and Machine Learning for People 2.11.2015

Contents

�  Paths of physical and mental wellbeing: from health to wellbeing & wellness interventions

�  Exploring Social isolation and loneliness: Are there loneliness types, how do people recover?

�  Citizen’s Mindscapes: Dynamics of emotions in social big data

Sports Institute of Finland (Vierumäki) fitness data

>100,000 measurements in 20+ years small subset with also mental workload & stress evaluation

(Vatanen, Heikkilä Honkela, Kettunen, Lagus &Pantzar, 2012)

males females

example: abdominals

all

40-50 years old

What kind of different ”fitness groups” can be found?

Relationship between physical & mental

wellbeing (stress)?

Do interventions help?

Map of fitness and stress

Individual wellbeing paths on the map of fitness and stress

Social isolation & loneliness �  Social isolation is a severe health risk both

physically and mentally �  Even brief ostracism appears to be experienced in the brain

as intense physical pain (Williams, 2011)

�  Continuous experience of pain is a continuous stress, leading to stress-related diseases

�  What different types of loneliness is there?

�  How do people recover from loneliness?

?

Text questions (in Yksinäisyyskysely 2011, 500 responses)

1.  Miten sinusta tuli yksinäinen? How did you become lonely?

2.  Miltä yksinäisyys tuntui? Miten se vaikutti mieleesi ja käyttäytymiseesi? How did it feel? How did it affect your mind and behaviour?

3.  Miten selvisit yksinäisyydestä (tai siitä huolimatta)? How did you survive loneliness (or despite it)?

4.  Tiesivätkö lähipiirisi ihmiset yksinäisyydestäsi? Miten he suhtautuivat siihen? Did people close to you know about your loneliness? How did they react?

5.  Mitä haluaisit sanoa muille vastaavassa tilanteessa oleville? What would you like to say to others in a similar situation?

Closed questions: During worst time of your life, did you feel

CONTENT ACCEPTED HAPPY

DEPRESSED SAD LONELY

CALM

(high value=red)

Closed questions: How (dis)content are you now with

(discontent=red) ONESELF FRIENDS

FREE TIME

FAMILY RELATIVES

LIVING STD WORK HEALTH

Segmenting loneliness (discontent=red)

family relationships support

completely alone

problems now: freetime, work, self, health, standard of living,

Problems with friends Problems with family

Krista Lagus, Juho Saari, Ilari T. Nieminen, and Timo Honkela. Exploration of loneliness questionnaires using the self-organising map. Proc. ICANN 2013, pp. 405–411, 2013.

Positive change in loneliness - what is happening?

LONELINESS LAST MONTH

LONELINESS IN WORST TIME OF LIFE

HAPPINESS LAST MONTH

Node 64, what helped: Professional help: psychotherapy/Aslak/perheasiain neuvottelu

Christ / spirituality /religion / god, found an amazing friend / some positive encounters running, crying, meeting my own emotions, forgiveness moving, hobbies, culture

Status now �  Network of loneliness researchers led by prof. Juho Saari collected a

27,000 people data set on loneliness (HS questionnaire 2014)

�  Tens of questions on various aspects of health, wellbeing and experienced loneliness

�  A text question: 3400 people answered “How does loneliness feel”?

�  Some initial experiments done – no funded project for systematically analyzing the data

�  Could we discover “loneliness types”?

�  Correlation btw written description of experienced loneliness and wellbeing indicators?

CITIZEN MINDSCAPES THE CHEMISTRY OF A NATION

AFFECTIVE CONTAGION: DISCOVERING

DYNAMICS OF EMOTIONS

Challenges �  How to recognize mass

emotions from texts?

�  How to detect the dynamic change of emotions within discussion threads?

�  Strategies and roles of discussants? Troll, Diplomat?

�  Sentiment analysis is challenging, typically positive/negative categories only obtained with sufficient accuracy

�  PERMA: 5-dimensional theory of wellbeing & associated vocabulary

�  Ad hoc: Vocabularies of emotional terms

�  Empirical linguistic theory of emotional expressions: Seija Tuovila dissertation on emotions (in Finnish)

Resources

�  Lack of knowledge on the mapping between felt emotions and textual expressions

�  National differences: Translation approaches may not be sufficient

Background: PERMA analysis of Big data conversations

0  

0,5  

1  

1,5  

2  

2,5  

3  

3,5  

4  

4,5  

ENRON Wikipedia EUROPARL

Positivity Meaning Achievement

Honkela, Korhonen, Lagus, Saarinen (2014). Five-dimensional sentiment analysis of corpora, documents and words. Proceedings of WSOM 2014.

EU (EUROPARL) discussions are full of meaning, low on talk how to achieve

ENRON corporate emails are positive and talk about concrete achievements but lack talk of meaning

VS  

Dynamics over time: Joy and Happiness peaks in 2005 and 2009

Data: about 3 million comments in suomi24, a nationally representative chat forum

Frequency analysis based on synonym dictionary definitions of emotions Searches using Korp.csc.fi

Discussion area profiles: where is most fear & worry?

Health Society

Relationships

Data: about 3 million comments in suomi24, a nationally representative chat forum

Frequency analysis based on synonym dictionary definitions of emotions Searches using Korp.csc.fi

Daily rythms

•  Lunchtime Activity Peak: At 11-12 lots of comments & lengthy

comments!

•  Fast-paced evening: 21-23 most new threads & comments, &

shortest comments

•  Hour of the Wolf: At 04-05 longest comments

•  Asleep: 05-06

0

1

2

3

4

5

6

7

1 3 5 7 9 11 13 15 17 19 21 23

Number of comments (24h) %

32

33

34

35

36

37

38

39

40

41

42

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 h

Word count per comment (24h)

0

1

2

3

4

5

6

7

1 3 5 7 9 11 13 15 17 19 21 23

Ketjujen aloituksia Kommentteja

Sanoja

%

Sanat, aloitukset ja kommentit (24h)

Data: 56 million posts of Suomi24

CITIZEN OBSERVATORY vs. EMPOWERING CITIZENS?

JOY-O-METER DATA: SUOMI24

Lagus, Pantzar, Ruckenstein (2015), “Keskustelun tunneaallot – Suomi24 -avoimen datan hanke. Tieteessä Tapahtuu, (in press)

Facebook group: Citizen Mindscapes


Recommended