Petr Lupač, Ph.D.

Charles University in Prague

World Internet Project

The Czech Republic

Financed due to Grant Agency of CZR (GA13-21024S)„World Internet Project – The Czech Republic II“

System of

social

inequality

Unequal

Internet access

Unequal

gains/losses

The empirical evidence?

Source: Van Dijk, J. A. G. M. (2005) Deepening digital divide: Inequality in the information society. Thousand Oaks.

CA: Sage, p. 22; simplified for purposes of presentation

Using the Internet can either improve or worsen people's lifes. When you think about your personal experience in the last years, how much influences your Internet use following areas of your life? Please, answer with the help of a scale, where -5 means significant worsening and +5 means significant improvement.

[Scale:]

-5 -4 -3 -2 -1 0 1 2 3 4 5

(-5=Significant worsening 5 = Significant improvement)

My knowledge of what's going on in the Czech republic

My knowledge of what's going on in other countries

My knowledge of what's going on in your locality

My involvement in public life in your local community

Dealing with state authorities {getting subsidy, welfare, submitting documents, etc.}

Contact with my family and my family life

Contact with my friends and acquiantences

My overall financial situation (i.e., your incomes and expenses)

Building up my career and my success on labor market

Pursuing and developing my hobbies

Overall satisfaction with my life

Rotated Component Matrixa

1 2 3 4 5 6 7

Change in knowledge, CZR ,239 ,858 ,139 ,090 ,042 ,085 ,124

Change in knowledge, world ,095 ,873 ,160 ,108 ,115 ,089 ,105

Change in knowledge, locality ,152 ,379 ,747 -,022 ,136 ,086 ,053

Change in involvement, local public life ,092 ,035 ,880 ,191 ,043 ,062 ,103

Change in dealing with state auth. ,121 ,139 ,110 ,116 ,117 ,954 ,061

Change in family life/contact ,840 ,062 ,115 ,189 -,005 ,112 ,074

Change in contact with friends ,797 ,252 ,070 -,115 ,167 ,076 ,163

Change in financial situation ,069 ,115 ,120 ,837 ,286 ,161 ,072

Change in career / labor market succ. ,098 ,130 ,131 ,243 ,918 ,122 ,065

Change in pursuing hobbies ,225 ,195 ,133 ,108 ,068 ,066 ,932

Change in overall satisfaction with life ,608 ,181 ,166 ,554 -,007 -,055 ,144

(4)

(5)

.

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 6 iterations74 % of variance (5 factors), 83 % of variance (7 factors)

The supposed role of variety/number of online activities and time spent online (van Dijk 2005)◦ -> hours online weekly, nr. of online non SNS activities performed weekly

The important role of digital skills, age and education in gaining benefits from Internet use (van Deursen, van Dijk and Peters 2011)◦ -> operational skills index, informational skills index, age, education

Previous social skills predict well sociability gains from Internet use (rich-get-richer hypothesis findings; c.f., Lee 2009)◦ -> ntw size index (via resource generator, sum of strong and weak ties)

The role of bridging social capital in acquiring resources◦ -> bridging = bonding * nr. of structural holes

The role of network capital in explaining individual state (Wellman and Frank 1999)◦ -> share of Internet users in respondent’s social environment

The ability to benefit from technological development (Rogers 2003)◦ -> innovativeness index

Donath & Boyd (2004)◦ SNS use linked to higher amount of weak ties

Ellison, Steinfiels & Lampe (2007)◦ The role of FB intensity of use, self-esteem and life satisfaction in predicting

higher bridging social capital◦ Compensation effect ◦ The role of FB intensity use confirmed by Steinfeld & Ellison (2008)

Valenzuela, Park & Kee (2009)◦ Intensity of FB use linked to higher life satisfaction and civic participation,

indirect link to social trust

Burke, Kraut & Marlow (2011)◦ The effect of FB use on bridging cpt. varies according to passive x active use◦ No relation between FB use and bonding cpt.

Lee, Noh & Koo (2013)◦ Indirect effect of SNS use for lonely people via establishing strong ties

online

0. SNS use and total gains from the Internet use are sig. correlated

0.1. SNS use and sociability gains from the Internet use are sig. correlated

0.2. SNS use and knowledge gains from the Internet use are sig. correlated

I. The intensity of SNS use predicts total gains from Internet use after controlling for other variables

II. The intensity of SNS use predicts sociability gains from Internet use after controlling for other variables

III. The intensity of SNS use predicts knowledge gains from Internet use after controlling for other variables

Pilot study in May

Data collected in May and June 2014 by a specialized agency

Method of data collection ◦ CAPI F2F interviews◦ Stratified random sampling combined with quota sampling ◦ Measures taken to include parts of the population with lower probability of being

interviewed Respondents declaring no or very low interest in being interviewed pre-recruited from CAWI

panel (cca 8 % of the sample) Trained experienced interviewers instructed to deal with soft-rejection Financial incentives (computed or estimated from wage) 100 % of the interviews were recorded, controlled and problematic respondents were excluded

1316 respondents in the final sample, 79 % Internet users

Weighted sample representative for the population of the Czech Republic, age 15+

A good fit of results with other data sources (WIP I, CZSO, Facebook)

Problem: We do not know the share of non-questioned busy people in a general population -> four steps to balance the sample

I. Weighting 92% of the sample (that was not pre-recruited) to fit the sociodemographic structure of the Czech population

II. Finding the relations between sociodemographics and Internet use/nonuse as well as the “pure” percentage of Internet users

III. Resulting Internet use added as a fixing variable to the weighting procedure

IV. Weighting the whole sample by the following auxiliary variables

Region (14 categories – NUTS3), Size of municipality (5 categories), Gender (2categories), Age (6 categories), Education (4 categories), Age x education (30 categories), Employment status (6 categories), Attended 2013 elections (2 categories)

◦ 5 iterations, weighting range: 0,5 – 2,0

Core questions◦ Frequencies of 35 online activities◦ Places of use, connection devices◦ Self-disclosure and privacy behavior and attitudes◦ Importance of the Internet as a source of entertainment and information

Digital skills◦ Operational, information, [strategic]

Social capital◦ proxy use, binding, bridging, network, structural holes, self-reported sociability

Cultural capital◦ Emerging, high-brow, reading books, active foreign language use

Political capital and behavior Innovativeness Internet indispensability Time online weekly Preference of online communication Experience with the Internet use/nonuse affecting quality of life in 7

dimensions

How often do you…A. Visit social networking sites (i.e., Facebook, Google+, Twitter, LinkedIn, Instagram)B. Post messages or comments on social networking sites, for example on Facebook or Twitter (if asked: also G+, Instagram, Linkedin, Lide.cz)

Possible answers: Several times a day, daily, weekly, monthly, less than monthly,

never

Transformations:◦ SNSuse index = A+B (Min=1, Max=12; Cronbach α= 0,84; mean=6,3; SD=3,7)◦ Logical types:

Daily users: visiting at least daily AND posting at least daily Nonusers: Visiting never OR visiting less than monthly OR Posting never Weak users: the rest

INDEX

Types of SNS users (% of CZR population 15+ ~ 8,9 mil.)Inet nonusers (21 %) SNS nonusers (40 %) SNS avg users (22 %) SNS daily users (17 %)

1,9 mil 3,5 mil. 2,0 mil. 1,5 mil.

0

20

40

1 2 3 4 5 6 7 8 9 10 11 12

35,8

27,2

4,8

3,6

7,9

4,2

11,2

9,7

10,3

14,2

8,7

19,9

POSTING

VISITING

Never Less than monthly Monthly Weekly Daily Several times a day

SNS NONUSERS (A) SNS AVG USERS (B) SNS DAILY USERS (C)

Age 50BC (14) 35C (14) 30 (10)

Nr. of close friends 5 (4) 6 (4) 6 (4)

Hours online /week 15 (16) 22A (20) 31AB(22)

Nr. of non-SNS onlineactivities least weakly

7 (4) 12B (5) 16AB (5)

Share of soc.environment using

the Internet70 % (20) 76 % (20) 84AB % (20)

Life satisfaction 7/10 (2) 8/10 (2) 8/10 (2)

Mean (SD)

ABC - stat. sig. differences at α=.01 (Tukey post-hoc test)

Dependent ⇢ Independent ⇣ Total change

Social contact change

Knowledge change

Gender 0,04 -,60 ,08*

Age -,96** -,09* -,03

Education ,11*** -,03 ,09**

SNS use intensity ,18*** ,21*** ,10**

SNSuse (users only) ,10* ,10* ,04

Skills operational ,21*** ,17*** ,10**

Skills informational ,30*** ,22*** ,24***

Innovativeness ,20*** ,18*** ,15***

OA variety – no SNS ,29*** ,24*** ,23***

Time on Internet /weak ,20*** ,15*** ,16***

Bridging soc. cpt. ,16*** ,08* ,10***

Ntw. size ,21*** ,16*** ,14***

Ntw. cpt ,26*** ,15*** ,21***

Life satisfaction ,19*** ,13*** ,09**

Model 1 Model 2 Model 3 Model 4

Age -,025 ,025 ,029 ,056

Education ,106** ,038 ,028 ,007

SNS use intensity ,145*** -,072 -,071 -,052

Time spent online ,057 ,055 ,039

OA variety - no SNS ,244*** ,251*** ,22***

Operational skills -,003 ,001 ,011

Informational skills ,253*** ,239*** ,197***

Innovativeness -,039 -,075

Life satisfaction ,126*** ,108**

Bridging cpt. ,079*

Ntw. Size ,06

Ntw. capital ,148***

Adj. R2 ,03 ,13 ,15 ,17

Model 1 Model 2 Model 3 Model 4

Age ,030 ,068 ,071 ,088*

Education -,019 -,059* -,078* -,092**

SNS use intensity ,209*** ,092 ,071 ,084

Time spent online ,041 ,025 ,012

OA variety – no SNS ,120** ,042 ,020

Operational skills ,000 ,029 ,022

Informational skills ,175*** ,162*** ,136***

Innovativeness ,029 ,003

Life satisfaction ,090** ,075*

OA comm no SNS 0,14** ,141**

Bridging cpt. ,023

Ntw. size ,084*

Ntw. capital ,085*

Adj. R2 ,04 ,07 ,09 ,10

Model 1 Model 2 Model 3 Model 4

Age -,020 -,012 -,018 -,001

Education ,106** -,012 ,010 ,001

SNS use intensity ,081* -,026 -,037 -,030

Time spent online ,037 ,013 ,004

OA variety -,082 -,099 -,104

Operational skills ,134*** ,128** ,124**

Informational skills -,246*** -,206* -,187***

OA info ,385*** ,366*** ,353***

Innovativeness -,009 -,032

Netinfo ,202*** ,193***

Persinfo ,065* ,072*

Bridging cpt. ,063*

Ntw. Size ,022

Ntw. capital ,085**

Adj. R2 ,02 ,16 ,20 ,21

Daily SNS users and SNS nonusers differ with respect to declared Internet-induced changes in their◦ Knowledge◦ Contact with friend◦ Life satisfaction

Intensity of SNS use does not appear to have a direct, independent effect on gains from Internet use

The strongest predictors in all three cases seem to be◦ informational digital skills◦ variety or intensity of other online activities◦ network capital

Better predictor than online activities variety seem to be intensity of relevant types of online activity

Petr Lupač, Ph.D.PETR.LUPAC@FF.CUNI.CZ

@PetrLupac

Department of Sociology

Charles University in Prague, Faculty of Arts

Celetna 13, Prague

The Czech Republic