CHARACTERISTICS FOR THEBEHAVIOR OF SOCIALNETWORKS USERS IN GERMANYby Knut Linke, Faculty of Economics and ManagementUniver...
Overview Milieu theory and lifeworlds Main hypothesis Analysing sub hypothesizes Results Recommondations
• According to (Bourdieu, 1980, p. 183), the society consists ofaccumulations which can only be represented by short-lived...
• This approach has also been used to research Internet users inGermany and Great Britain (Lichy, 2011, pp. 470-475), andd...
In order to confirm the theoretical fundamentals the following (primary)hypothesis has been proposed:•H: The consideration...
In the following the first results of the main analyses of the ISS2012 (892female and 715 male participants; the average y...
• SH1: An increasing household income has a positive and significantimpact on the living environment of the participant.• ...
• SH1b: There is a significant correlation of at least ρ > +0.3 betweenthe household income and its residential environmen...
• SH2: There is a significant and positive correlation between particularmedia content and gender.• SH2a: There is a signi...
• SH2c: There is a significant correlation of at least ρ > +0.3 betweenthe male participants and consumption of TV content...
• SH3: There is a highly significant correlation of at least ρ > +0.5between the duration of Internet use during the week ...
• SH3b: There is a highly significant correlation of at least ρ > +0.5between the duration of using the Internet on a mobi...
• There is an SRCC of -.068/-.001 between using the Internet on adesktop computer during the week and using the Internet o...
• SH5: There is a significant correlation between social networks andthe intensity of their use.• SH5a: There is a signifi...
• SH5b: Significant factors consisting of social networks can be defined.• The factor analysis (KMO .915; Sig. by Bartlett...
• SH7: There is a significant correlation between the intensity of usingbusiness networks, specific users and the factors ...
• SH7b: There is a significant correlation of at least ρ > +0.3 betweenthe intensity of using business networks and the mo...
• SH7c: There is a significant correlation of at least ρ > +0.3 betweenthe motivation to find business partners and custom...
• SH7e: A significant factor can be defined for the functions of SH7a-SH7d.• Factor No 5, provided by factor analysis (KMO...
• SH7f: There is a significant correlation of at least ρ > +0.3 between theintensity of using business networks and the ed...
• UH7a-UH7g indicates a very specific situation regarding the users ofbusiness networks.• SH7b was not confirmed, but it s...
• SH8: There is a significant correlation between the intensity of usingthe Internet for political discussions and the int...
• SH8b: There is a significant correlation of at least ρ > +0.3 betweenthe motivation to hold political discussions and to...
• SH8d: A significant factor can be defined for the functions of SH8a-SH8c.• Factor analysis (KMO .914; Sig. by Barlett .0...
• SH10: There is a significant correlation of at least ρ > +0.3 betweenthe users degree of interest in listening to music ...
• The results of the analyses display a positive and homogeneous trend.• In general, it is evident that the findings of th...
• There is a strong emphasis in the results on youngparticipants.• This raises the question if the hypotheses would exist ...
• In light of SH1 and SH10, the results allow expressing the first generalrecommendations.• If there is a correlation betw...
• (Becker et al., 1992) Horst Becker, Ulrich Becker, Walter Ruhland:Zwischen Angst und Aufbruch, ECON, Düsseldorf, 1992 [2...
THANK YOU FOR YOUR ATTENTION
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Characteristics for the behavior of german social networks users

  1. 1. CHARACTERISTICS FOR THEBEHAVIOR OF SOCIALNETWORKS USERS IN GERMANYby Knut Linke, Faculty of Economics and ManagementUniversity of Latviaat the International Conference:NEW CHALLENGES OF ECONOMIC AND BUSINESS DEVELOPMENTMay 9-11, 2013, Riga, University of Lativa
  2. 2. Overview Milieu theory and lifeworlds Main hypothesis Analysing sub hypothesizes Results Recommondations
  3. 3. • According to (Bourdieu, 1980, p. 183), the society consists ofaccumulations which can only be represented by short-lived andmechanical states of equilibrium.• (Schulze, 1992, pp. 176-197) supports this approach of stipulating andchoosing relationships on the basis of the character and shape. Theterm social milieu (Becker et al., 1992, p. 80) combines groups ofpeople who are similar in terms of their outlook on life and life style.Consequently, the group has the same living environment (Hradil,2006, pp. 87-125).• The term social milieu (Hradil, 2006, pp. 278-284) denotes agrouping of people that have a similar mentality and often a commonfactual context (region, district, professional life, etc.).Milieu theory and lifeworlds
  4. 4. • This approach has also been used to research Internet users inGermany and Great Britain (Lichy, 2011, pp. 470-475), anddifferences in the online communication behaviour can be observed.• The social differentiation, that is, the connection between personalpreferences, the social position and the benefits from the use of theInternet and social networks, has so far not been investigated in theFederal Republic of Germany.• An estimate of the number of users of a population can be obtainedfrom the approach of social structure analysis. The population can beanalysed in terms of certain forms or market segments.Milieu theory and lifeworlds
  5. 5. In order to confirm the theoretical fundamentals the following (primary)hypothesis has been proposed:•H: The consideration of a participant’s lifeworld leads to more reliable resultsthan analysing the sample without taking lifeworlds into account.supported by three main-sub-hypothesis (build on pre-research):•Ha: The selected lifeworlds reveal characteristics, relating to their consumptionpreferences, which can be described as typical for the respective lifeworld.•Hb: The lifeworlds show characteristics, relating to the use of the Internet, whichcan be described as typical for the respective lifeworld.•Hc: In a direct comparison of the milieus, the selected lifeworlds reveal significantchanges in the results of the SH1-SH10.Researched hypothesis
  6. 6. In the following the first results of the main analyses of the ISS2012 (892female and 715 male participants; the average year of birth: 1983,median: 1987, mode: 1991; Internet since average: 2000 median: 2001;431 of the 1,607 participants did not have mobile Internet access;average income level of 35,000 - 44,999€; average number of personsper household is 2.62, median/mode of 2) sample for the hypothesis “Hc:In a direct comparison of the milieus, the selected lifeworlds revealsignificant changes in the results of the SH1-SH10” are displayed.The Hc is researched with a selection of six out of the ten sub-hypothesizes with the statistical methods of product-moment correlation(PMC) by Pearson, Spearmans rank correlation coefficient (SRCC) andfactor analysis.Analyses
  7. 7. • SH1: An increasing household income has a positive and significantimpact on the living environment of the participant.• SH1a: There is a significant correlation of at least ρ > -0.3 between thehousehold income and the time when an Internet connection isinstalled in the household.• The SRCC shows a value of -.306 between the variables of householdincome and the beginning of Internet use. This means that the higherthe gross income of a household, the sooner it started using theInternet. SH1a can be considered as confirmed.Sub-hypothesis 1
  8. 8. • SH1b: There is a significant correlation of at least ρ > +0.3 betweenthe household income and its residential environment.• An SRCC of +.401 exists between the variables of household incomeand the residential environment. SH1b can be considered asconfirmed.• SH1c: There is a significant correlation of at least ρ > +0.3 betweenthe household income of the participant and his educationalqualification.• The SRCC shows a value of +.299 between the variables of householdincome and the educational qualification. Unfortunately, SH1ccannot be considered as confirmed (formally)• SH1 can be considered as confirmed, if the +.299 would be count as+.3Sub-hypothesis 1
  9. 9. • SH2: There is a significant and positive correlation between particularmedia content and gender.• SH2a: There is a significant correlation of at least ρ > +0.3 betweenthe female participants and consumption of romantic films.• A PMC/SRCC of +.458 can be observed between the gender of theparticipant and the preference for romance films. SH2a can beconsidered as confirmed.• SH2b: There is a significant correlation of at least ρ > +0.3 betweenthe male participants and consumption of action films.• A PMC/SRCC of +.342 can be detected between participants of themale gender and the preference for action films. SH2b can beconsidered as confirmed.Sub-hypothesis 2
  10. 10. • SH2c: There is a significant correlation of at least ρ > +0.3 betweenthe male participants and consumption of TV content relating tosports.• There is a PMC/SRCC of +.331 between the male participants and thepreference for TV content relating to sports. SH2c can be consideredas confirmed.• SH2d: There is a significant correlation of at least ρ > +0.3 betweenthe female participants and consumption of romantic literature.• There is a PMC/SRCC of +.387 between the female participants andthe preference for romance literature. This confirms the assumptionsthat romance literature, as well as romance films, are usually enjoyedby women. SH2d can be considered as confirmed.• SH2 can be considered as confirmed.Sub-hypothesis 2
  11. 11. • SH3: There is a highly significant correlation of at least ρ > +0.5between the duration of Internet use during the week and at theweekend.• In the following, the values refer first to a population of n=1,607,including all participants, and a population of n=1,177, including theparticipants who indicated the availability of mobile Internet.• SH3a: There is a highly significant correlation of at least ρ > +0.5between the duration of using the Internet on a desktop computerduring the week and at the weekend.• There is a highly significance SRCC value of -.724/-.745 between usingthe Internet on a desktop computer during the week and at theweekend. SH3a can be considered as confirmed.Sub-hypothesis 3
  12. 12. • SH3b: There is a highly significant correlation of at least ρ > +0.5between the duration of using the Internet on a mobile device duringthe week and at the weekend.• There is an SRCC of +.864/+.776 between using the Internet onmobile device during the week and at the weekend. SH3b can beconsidered as confirmed.• SH3c: There is no correlation of at least ρ > +0.3 between the durationof using the Internet on a desktop computer or a mobile device.• There is an SRCC of -.051/+.045 between using the Internet on adesktop computer during the week and a mobile device during theweek.Sub-hypothesis 3
  13. 13. • There is an SRCC of -.068/-.001 between using the Internet on adesktop computer during the week and using the Internet on amobile device at the weekend. There is an SRCC of -.061/+.011between using the Internet on a desktop computer at the weekendand using the Internet on a mobile device during the week. There isan SRCC of -.030/+.139 between using the Internet on a desktopcomputer at the weekend and using the Internet on a mobile deviceat the weekend. In addition, there is no significance of themeasurements, or a significance of the level of 0.01. SH3c can beconsidered as confirmed.• SH3 can be considered as confirmed.Sub-hypothesis 3
  14. 14. • SH5: There is a significant correlation between social networks andthe intensity of their use.• SH5a: There is a significant correlation of at least ρ > +0.3 betweensocial networks with the same user layers.• SH5a can be considered as confirmed.Sub-hypothesis 5(1) (2) (3) (4) (5) (6) (7) (8)Flickr (1) 1 +.385 +.406 +.420 +.372 +.353 +.282 +.3634SQ (2) +.385 1 +.408 +.276 +.419 +.400 +.267 +.431Instagram (3) +,406 +.408 1 +.314 +.245 +.361 +.329 +.373LastFM (4) +.420 +.276 +.314 1 +.247 +.295 +.355 +.280LinkedIn (5) +.372 +.419 +.245 +.247 1 +.390 +.208 +.338Pinterest (6) +.353 +.400 +.361 +.295 +.390 1 +.317 +.297Spotify (7) +.282 +.267 +.329 +.355 +.208 +.317 1 +.232Twitter (8) +.363 +.431 +.373 +.280 +.338 +.297 +.232 1
  15. 15. • SH5b: Significant factors consisting of social networks can be defined.• The factor analysis (KMO .915; Sig. by Bartlett .000) shows threefactors:• The first factor contains mainly niche networks and is led by certainnew networks which focus on special users groups or web functions.• The second factor consists mostly of older networks or networkswhich are not evident in the correlation analysis.• The third factor contains niche networks from Germany which are nolonger on the market with an impact on it.• SH5b can be considered as confirmed.• SH5 can be considered as confirmed.Sub-hypothesis 5
  16. 16. • SH7: There is a significant correlation between the intensity of usingbusiness networks, specific users and the factors motivating them touse business networks.• SH7a: There is a significant correlation of at least ρ > +0.3 betweenthe intensity of using business networks and the motivation to findbusiness partners and customers.• Both networks (Xing and LinkedIn) have a PMC which exceeds +.3.There is a PMC of +.372 for LinkedIn and +.434 for Xing and themotivation to search for customers and business partners. SH6a canbe considered as confirmed.Sub-hypothesis 7
  17. 17. • SH7b: There is a significant correlation of at least ρ > +0.3 betweenthe intensity of using business networks and the motivation to searchfor jobs using social networks.• There is a correlation of +.268 between LinkedIn and job search, and+.305 between Xing and job search. Due to the fact that bothnetworks are very similar and no such correlations can be seen forother networks, it is assumed that career change is a motivationalfactor for using Xing and LinkedIn. SH6b is formally regarded asunconfirmed. Nevertheless, a notable correlation exists; especiallyXing exceeds the significant limit.Sub-hypothesis 7
  18. 18. • SH7c: There is a significant correlation of at least ρ > +0.3 betweenthe motivation to find business partners and customers and to searchfor jobs using social networks.• There is a PMC of +.470 between both motivations. SH6c can beconsidered as confirmed.• SH7d: There is a significant correlation of at least ρ > +0.3 betweenthe motivation to find business partners and customers and toestablish contacts within social networks.• There is a PMC of +.368 between both motivations. Establishingcontacts in social networks has a PMC of +.199 for LinkedIn and +.220for Xing. SH6d can be considered as confirmed.Sub-hypothesis 7
  19. 19. • SH7e: A significant factor can be defined for the functions of SH7a-SH7d.• Factor No 5, provided by factor analysis (KMO .915; Sig by Barlett .000) is led by the search for business partners with a loading of +.668,and followed by the use of networks for job search with +.608, theintensity of using of Xing with +537, LinkedIn with +454, and theintention to establish contacts with +.412. SH6e can be considered asconfirmed.Sub-hypothesis 7
  20. 20. • SH7f: There is a significant correlation of at least ρ > +0.3 between theintensity of using business networks and the educational qualificationof the user.• There is an SRCC of +.324 between LinkedIn and the educationalqualification of the participant. There is an SRCC of +.409 betweenXing and the educational qualification of the participant. SH6f can beconsidered as confirmed.• SH7g: There is a significant correlation of at least ρ > +0.3 betweenXing and LinkedIn.• There is a highly significant PMC of +.559 between the intensity of theuse of both business networks Xing and LinkedIn. SH7g can beconsidered as confirmed.Sub-hypothesis 7
  21. 21. • UH7a-UH7g indicates a very specific situation regarding the users ofbusiness networks.• SH7b was not confirmed, but it shows a clear trend for the Germanmarket. This raises the question of how similar the significance ofLinkedIn and Xing is. Based on the measured significance, a highsimilarity can be expected. It can be expected that here by a specialityfor German users exists, which focusses the usage of those networksmore work related as users with a more international mind.• The rest of the sub-hypotheses were confirmed. Therefore, SH7 canbe regarded as confirmed if the hypothesis focusses on the Germanmarket of business networks only. For an international approach theSH7 cannot be considered as confirmed.Sub-hypothesis 7
  22. 22. • SH8: There is a significant correlation between the intensity of usingthe Internet for political discussions and the intensity of usingcommunication functions.• SH8a: There is a significant correlation of at least ρ > +0.3 betweenthe motivation to hold discussions relating to politics and the intensityto leave comments.• The correlation for the commenting of content has only a PMC of+.294 and making comments in general has the value of +.238,discussing events shows a PMC of +.249.• SH8a is regarded as unconfirmed.Sub-hypothesis 8
  23. 23. • SH8b: There is a significant correlation of at least ρ > +0.3 betweenthe motivation to hold political discussions and to exchange opinions.• There is a PMC of +.442 for the intensity of the motivation toexchange opinions. SH8b can be considered as confirmed.• SH8c: There is a significant correlation of at least ρ > +0.3 betweenthe motivation to hold discussions relating to politics and to shareweb-sites within social networks.• There is a PMC of +.315 between the motivation to discuss politicalcontent and the intensity to share websites on social networks. SH8ccan be considered as confirmed.Sub-hypothesis 8
  24. 24. • SH8d: A significant factor can be defined for the functions of SH8a-SH8c.• Factor analysis (KMO .914; Sig. by Barlett .000) indicates a factor, ledby the motivation to discuss the daily events with a loading of +.688,and followed by discussing politics with a loading of +632, discussingTV content with +.457 and exchanging opinions with +.386. SH8d canbe considered as confirmed.• SH8 basically shows that politically active people, who share contentrelated to politics, are generally of communicative nature and shareother types of content as well. Formally, SH8 cannot be consideredas confirmed, since SH8a was not confirmed.Sub-hypothesis 8
  25. 25. • SH10: There is a significant correlation of at least ρ > +0.3 betweenthe users degree of interest in listening to music as a leisure activityand the intensity of taking part in online services which offer music.• As concerns leisure activities, listening to music and listening to musicon the Internet has a PMC of +.486. In addition, leisure activitiescorrelate with watching videos on the Internet with a value of +.294.• There is a highly significant correlation of +.509 between listening tomusic on the Internet and watching videos on the Internet.• In addition, there is a correlation of +.300 between listening to musicon the Internet and consuming TV content on the Internet.• SH10 can be considered as confirmed.Sub-hypothesis 10
  26. 26. • The results of the analyses display a positive and homogeneous trend.• In general, it is evident that the findings of the preliminary researchcan be proved. The results also made it possible to gather a largenumber of online and offline behaviours, and to make specificassertions concerning the examined user layer.• In addition to the discussed SHs, three additional SH, related toFacebook usage, usage of security settings and music consumption,could be confirmed. The results must be viewed, however, againstthe validity of the sample.• The confirmed SH10 shows an example that it is possible to transfercertain types of leisure activities to the Internet.Results
  27. 27. • There is a strong emphasis in the results on youngparticipants.• This raises the question if the hypotheses would exist indifferentiated lifeworlds or there would be shifts.• Focus was on the target group of social network users.• The survey was only provided online, the results can be differentif they would be done offline• Only valid for German usersLimitations
  28. 28. • In light of SH1 and SH10, the results allow expressing the first generalrecommendations.• If there is a correlation between the availability of financial means and the abilityto use the Internet, as demonstrated by SH1, Internet access should be granted topeople in order to avoid discrimination caused by a lack of finances.• Moreover, SH8 shows, with certain significance, that people use the Internet todiscuss issues related to politics. This can be important for a country to maintaindemocracy and provide its people with the opportunity for open discussion.• There should be a political demand, proved by statistical data, for afree, government-guaranteed Internet access, and no restrictionsshould be imposed on it. As concerns the degree to which a stateneeds to protect itself and its citizens, a generally free access to theInternet, in view of a democratic society, should not be limited.Recommendations
  29. 29. • (Becker et al., 1992) Horst Becker, Ulrich Becker, Walter Ruhland:Zwischen Angst und Aufbruch, ECON, Düsseldorf, 1992 [230 P.].• (Bourdieu, 1980) Pierre Bourdieu: Sozialer Sinn, Suhrkamp, Frankfurton the Main, 1980 [503 P.].• (Hradil, 2006) Stefan Hradil: Die Sozialstruktur Deutschlands iminternationalen Vergleich, 2nd edition, VS, Wiesbaden, 2006 [304 P.].• (Lichy, 2011) Jessica Lichy: Internet user behavior in France andBritain: exploring socio-spatial disparity among adolescents, In:International Journal of Consumer Studies, No. 35, 2011 [PP. 470-475].• (Schulze, 1992) Gerhard Schulze: Die Erlebnisgesellschaft, Campus,Frankfurt, 1992 [765 P.].References
  30. 30. THANK YOU FOR YOUR ATTENTION

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