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Friendships and CMC Friendships and CMC

Consequences of media and Internet use for offline and online network capital and well-being. Consequences of media and Internet use for offline and online network capital and well-being. A causal model approach • Sought to test the following hypotheses: – H 1: “The more time people spend on watching television, the less time they spend on socializing with other people” – H 2: “The more time people spend on entertainment websites, the less time they spend socializing with other people” – H 3: “The more time people spend on visiting information websites, the more time they spend on socializing with others” – H 4: “The more time people spend on websites for practical purposes, the more time they spend socializing with other people”

Consequences of media and Internet use for offline and online network capital and well-being. Consequences of media and Internet use for offline and online network capital and well-being. A causal model approach • H 5: “The larger the offline network is, the larger the online network is” • H 6: “The more time people spend on their online social network, the less time they spend on their offline social network” • H 7: “The larger the social network is, the more time people spend socializing with others”

Consequences of media and Internet use for offline and online network capital and well-being. Consequences of media and Internet use for offline and online network capital and well-being. A causal model approach • H 8: “The larger people’s social network is, the more social support they experience” • H 9: “The more time people spend on socializing with others, the less lonely they feel” • H 10: “The more social support people experience, the less lonely they are”

Consequences of media and Internet use for offline and online network capital and well-being. Consequences of media and Internet use for offline and online network capital and well-being. A causal model approach • Method: • Respondents were drawn from a random sample of household landlines in the Netherlands • Had to be users of Internet for reasons in addition to work related activities to participate in most of the interviews • A very strange distribution: • “The offline subsample (N = 714) consisted of people who did not use the Internet for private purposes. The online sample (N = 96) consisted of people that were using the Internet for nonwork-related purposes. ” confusion in that they were sorted by this question, yet the data indicate that the “offline” sample answered questions about surfing the web for entertainment and informational content • Conducted interviews by phone

Consequences of media and Internet use for offline and online network capital and well-being. Consequences of media and Internet use for offline and online network capital and well-being. A causal model approach

Consequences of media and Internet use for offline and online network capital and well-being. Consequences of media and Internet use for offline and online network capital and well-being. A causal model approach • Sought to test the following hypotheses: – H 1: “The more time people spend on watching television, the less time they spend on socializing with other people” NOT CONFIRMED – H 2: “The more time people spend on entertainment websites, the less time they spend socializing with other people” NOT CONFIRMED (a positive effect on time spent on the online social network but no effect on offline capital size and time) – H 3: “The more time people spend on visiting information websites, the more time they spend on socializing with others” CONFIRMED for online network capital – H 4: “The more time people spend on websites for practical purposes, the more time they spend socializing with other people” NOT CONFIRMED

Consequences of media and Internet use for offline and online network capital and well-being. Consequences of media and Internet use for offline and online network capital and well-being. A causal model approach • H 5: “The larger the offline network is, the larger the online network is” NOT CONFIRMED • H 6: “The more time people spend on their online social network, the less time they spend on their offline social network” NOT CONFIRMED • H 7: “The larger the social network is, the more time people spend socializing with others” CONFIRMED

Consequences of media and Internet use for offline and online network capital and well-being. Consequences of media and Internet use for offline and online network capital and well-being. A causal model approach • • • H 8: “The larger people’s social network is, the more social support they experience” CONFIRMED for offline sample but not for online sample H 9: “The more time people spend on socializing with others, the less lonely they feel” NOT CONFIRMED although the relationship between offline network size and loneliness is mediated by social support H 10: “The more social support people experience, the less lonely they are” CONFIRMED Generally support for rich get richer rather than substitution or displacement Online network may mirror offline but there’s no evidence that a lot of the commuication is carried out through it (as opposed to merely mapping or displaying it) Online network capital doesn’t seem to translate into increased social support, but offline does

Inferring Social Network Structure using Mobile Phone Data • Conventional social network analysis studies Inferring Social Network Structure using Mobile Phone Data • Conventional social network analysis studies limited by reliance on self-report data and limited sample sizes • The authors use three types of information mobile phones: communication (via call logs), location (via cell towers), and proximity to others (via repeated Bluetooth scans). • 330, 000 hours of these behavioral observations from 94 subjects over nine months – Still a small N by their standards but certainly enough behavioral observations to be reliable measurement – Collected behavioral data and they also filled out self-report instruments on proximity to and friendship with others, and satisfaction with work – Were largely coworkers working in the same building – Given a free smartphone to participate – The self-report data is not impressive; did not use standard measures, no reliability estimat

Inferring Social Network Structure using Mobile Phone Data • Distinction between a behavioral relation Inferring Social Network Structure using Mobile Phone Data • Distinction between a behavioral relation between members of a dyad and a cognitive relation (a belief of some sort about the nature of the relationship) • These often diverge. Does their divergence constitute interesting data? Or is it merely noise? (measurement error) • Studies – Relationship between Behavioral and Self-Report Data • Observed actual proximity at work was related to self-reports, but the best predictor of self-reported proximity at work was actual proximity outside work

Inferring Social Network Structure using Mobile Phone Data • Behavioral Characteristics of Friendships – Inferring Social Network Structure using Mobile Phone Data • Behavioral Characteristics of Friendships – “constructed seven dyadic behavioral variables: volume of phone communication and six contextualized variants of proximity” “for all the dyadic behavioral variables, reciprocal friends score far higher than reciprocal non-friends (subjects who work together but neither considers the other a friend)” – Seem to be two underlying factors, proximity at work and proximity outside of work – Claim to be able to predict 95% of reciprocal friendships based on the behavior data alone – What about texting? I think texting behavior is a better indicator than phone calls, depending on the age of the study cohort

Inferring Social Network Structure using Mobile Phone Data • Predicting satisfaction based on behavioral Inferring Social Network Structure using Mobile Phone Data • Predicting satisfaction based on behavioral data • Work group satisfaction significantly predicted by number of friends, but model strengthened by adding in average daily proximity to friends (positive relationship) and average phone communication with friends (negative relationship? Why? ) in fact, the self-report friendship data are not really necessary as the behavioral data can be used to effectively explain variance in friendship relations

Inferring Social Network Structure using Mobile Phone Data • • Closer look at the Inferring Social Network Structure using Mobile Phone Data • • Closer look at the data: “The majority (69%) of the observed average proximity of over 5 minutes/day was not reported. However when proximity was reported, it was typically overestimated” “average proximity outside of work, at home, and on Saturday night all independently and powerfully predict reported proximity at work, controlling for observed proximity at work” -they think of this as an effect of “saliency” where you’re estimating something based on the availability of a particular cue or its seeming relevance in context- being together outside of work seems to be especially salient both observed average proximity and recent proximity are significant predictors of reported proximity

Inferring Social Network Structure using Mobile Phone Data Phone communication the best predictor of Inferring Social Network Structure using Mobile Phone Data Phone communication the best predictor of friendship although all but one were significant

Inferring Social Network Structure using Mobile Phone Data • • “Both in-role …(e. g Inferring Social Network Structure using Mobile Phone Data • • “Both in-role …(e. g work related) …and extra-role communication are strongly predictive of friendship. After a promax rotation on the factor scores, a threshold of 2. 3 on extra-role communication correctly classifies 19/20 (95%) reciprocal friends and 901/935 (96%) reciprocal nonfriends. Using a threshold of. 57 on in-role communication, we correctly classify 19/20 (95%) reciprocal friends and 868/935 (93%) reciprocal non-friends. While there were no thresholds that could identify the non-reciprocal friend dyads with these levels of accuracy, we show below that non-reciprocal dyads do form a group that behaviorally falls between reciprocated friend and non-friend dyads—perhaps reflecting that friendship is a continuous variable rather than bivariate” Re predicting work satisfaction-there is a weak relationship between satisfaction and number of friends Prediction improves significantly after adding average proximity to friends and phone communication with friends.

Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence

Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence

Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence

Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence

Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence

Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence Patterns of media use and multiplexity: Associations with sex, geographic distance and friendship interdependence

Chan and Cheng (2004). A comparison of offline and online friendship qualities at different Chan and Cheng (2004). A comparison of offline and online friendship qualities at different stages of relationship development. • Cues-filtered-out approaches • CMC is hypothesized to be lower in information richness (Sproull and Kiesler) and social presence (Short, Williams and Christie) than f 2 f and theoretically should be less well suited to support interpersonal relationships • Walther argues and shows that given enough time and message exchange relational intimacy can develop through CMC to the same extent it does in f 2 f • Present study focuses on comparing friendship qualities between offline and online friendships at different stages of development

Chan and Cheng (2004). A comparison of offline and online friendship qualities at different Chan and Cheng (2004). A comparison of offline and online friendship qualities at different stages of relationship development. • Hypotheses (sort of) • “we expected that the overall qualities of offline friendships would be higher than those of online friendships. … • the qualities of both online and offline friendships would improve over time…. . • the differences between offline and online friendships were expected to become smaller as the relationship progressed”

Chan and Cheng (2004). A comparison of offline and online friendship qualities at different Chan and Cheng (2004). A comparison of offline and online friendship qualities at different stages of relationship development. • Cross-sex friendships are more difficult to develop because of status inequalities, lack of natural opportunities for fraternization, concern over sexual issues • Although most offline friendships are same sex, most online friendships are cross-sex • Further predicted that differences in friendship qualities that obtain for f 2 f cross sex and samesex friendships will be less striking for online friendships

Chan and Cheng (2004). A comparison of offline and online friendship qualities at different Chan and Cheng (2004). A comparison of offline and online friendship qualities at different stages of relationship development. • Method – Subjects were recruited from a Hong Kong newsgroup – They were asked to fill out a survey while thinking of two friends, one an offline friend and one an online friend – They completed questionnaires that assessed the relationships on seven qualities: interdependence, depth, breadth, code change, understanding, commitment, network convergence (reliabilities were sort of low, in the 60 s and 70 s, for most of their measures) • Results – Analysis was a 2 (Friendship Type: offline vs. online) by 3 (Duration: 1– 4 months vs. 5– 12 months vs. over 1 year) by 2 (Gender Composition: same-sex vs. cross-sex friendship) MANOVA – Significant main effects for all three factors were qualified by several significant two-way interactions

Chan and Cheng (2004). A comparison of offline and online friendship qualities at different Chan and Cheng (2004). A comparison of offline and online friendship qualities at different stages of relationship development. • Main effect for relationship type such that relational quality was rated higher on all seven dimensions for offline than online friendships • These differences tended to increase up until about one year of friendship, however, these differences were minimal for friendships that lasted more than a year • Consistent with Walther’s social information processing theory in that given sufficient time enough messages will be exchanged to compensate for the lack of social presence available in CMC • Gender effect such that for offline friendships, same sex had higher quality but for online, cross-sex friendships were higher in relationship qualities – Internet removes constraints that impede development of opposite sex friendships in f 2 f • Authors noted that a limitation of their study was that they did not really have any control over whether or not the online friends had any offline contact, although the instructions explicitly stated that the online friend should be online only

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • There is some limited amount of data indicating that having a number of online friends can contribute to a sense of well-being or is especially helpful to shy people in reducing their social anxiety • Opinions on whether time spent online or time spent with online friends helps to reduce loneliness vary across studies or even across time within the same research team (e. g. Kraut group)

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • Recent article from Kraut and colleagues (Bessier, Kiesler, Kraut & Boneva) looked at the impact of Internet use on well-being, specifically depression – They identified three main schools of thought about the impact of Internet use on psychosocial variables and friendship networks • The social augmentation hypothesis- Internet provides an additional channel for everyday relational maintenance plus it expands opportunities for expanding the social network – Many studies that reach this conclusion don’t address preexisting differences between Internet users and non-users in terms of their offline social networks

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • The social displacement hypothesis-that internet use substitutes for time spent with family and friends with a resulting negative effect on well-being – In this view, online and offline social networks are not interchangeable and do not provide equivalent psychosocial benefit – Again, a lot depends on the nature of the individual’s social networks – With IT so firmly integrated into contemporary life, there’s ample evidence that it helps users to manage their time with family and friends more efficiently and keep up in the absence of time to spend f 2 f • The social compensation hypothesis (Mc. Kenna & Bargh) –using Internet for making and keep friends has augmentative effects for people whose social networks were impoverished to begin with

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • Result from a reanalysis by Bessier, Kiesler, Kraut & Boneva of data from an earlier study on internet use and depression (data was longitudinal, 2000 and 2001) – People who used the internet to communicate with family and friends had lower entering scores on depression and were more likely to experience less depression over time – People who used the Internet to meet others were likely to have increases in depression, and this effect was particular manifest among people with higher levels of social support, and not those with lower levels

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • The authors of the current paper cite a prior study which showed that participation in a MUD could be a useful tool for increasing social efficacy of shy individuals • Cite a further study showing that the impact of interacting with cyberfriends on social skills and well-being varied with whether or not the friends were same-sex (greater social efficacy) or opposite sex (greater happiness) (although all their subjects were male) • Some studies have found that loneliness as measured by UCLA Loneliness Scale is associated with time spent with women friends – Women who had boyfriends were found to feel significantly more lonely than women who did not have boyfriends – Same effect not found for men – Time spent disclosing to women thought to be the operative factor

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • Many theoretical approaches to online relationships, especially the early ones, have evolved from conceptions of CMC as largely textbased and hence lean with respect to visual, paralinguistic and contextual cues – This causes people to fill in the blanks, which, over time, may result in idealized representations of online partners (hyperpersonalism) based in part on limited and largely self-promoting information from the partner – Cue scarcity may increase the salience of social identity markers and create bonds on the basis of shared social category membership – Such theories start to lose relevance as we increasingly encounter people online in multimedia environments where context is provided by their transparent social networks YET STILL • At issue is the reliability of the network information given the looseness of the definitions of friends, contacts, etc. • Further at issue are the greater degree of control over self-presentation which online environments provide – Given applications like Skype there is little reason for improverished environments for communication where nonverbal and paralinguistic cues are absent

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • For people who take a dim view of their own physical attractiveness, online friendships may offer an opportunity to build relationships free of the tyranny of having to look good to potential friends and partners • Being able to be judged on the personality projected rather than looks may help people to overcome the kinds of social phobias that would keep them from interacting socially in a relaxed and receptive manner • Expectation was that for persons who were less assured about their physical attractiveness, making friends online would have a more profound effect on their feelings of loneliness and social anxiety and that these effects would be more pronounced when the friends were opposite sex rather than same sex (this seems to assume that all subjects would be reacting in the same way to the opposite sex as a potential source of romantic partners)

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • “Hypothesis A: Having a large number of cyberfriends would lower social anxiety felt by the low self-evaluated attractiveness group. – Also, such effects would be more prominent if the cyber-friends were of the opposite sex. • Hypothesis B: Having a large number of cyberfriends would reduce the loneliness felt by the low self-evaluated attractiveness group. – Also, such effects would be more prominent if the cyber-friends were of the opposite sex. ”

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • examined three types of loneliness: in friendships, in family relationships, and in society • Method – Subjects were 178 Japanese undergraduates, about 2/3 women – Data collected in a two-wave panel study, October 2000, January 2001 (enough time elapsed to see causal effects? ) – Survey contained items on number of cyber-friends, selfevaluation of physical attractiveness, social anxiety, loneliness, and demographic data – With respect to loneliness, wrote some new measures for the study to assess the multidimensional nature of the construct they were measuring, as well as incorporating some items from the UCLA scale (see next slide for UCLA scale) Russell, D. (1996). The UCLA Loneliness Scale (Version 3): Reliability, validity, and factor structure. Journal of Personality Assessment, 66, 20 -40.

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups 1. How often do you feel unhappy doing so many things alone? O S R N 2. How often do you feel you have nobody to talk to? O S R N 3. How often do you feel you cannot tolerate being so alone? O S R N 4. How often do you feel as if nobody really understands you? O S R N 5. How often do you find yourself waiting for people to call or write? O S R N 6. How often do you feel completely alone? O S R N 7. How often do you feel you are unable to reach out and communicate with those around you? O S R N 8. How often do you feel starved for company? O S R N 9. How often do you feel it is difficult for you to make friends? O S R N 10. How often do you feel shut out and excluded by others? O S R N

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • Findings – Low and high self-attractiveness groups (mean split- a good idea? ) were significantly different on all three measures of loneliness, with low self-attractiveness group higher on loneliness – Did not differ on social anxiety or number of online friends

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups The data were examined separately for the high and low selfattractiveness groups Path E behaved differently for the two groups For the Low group, lots of cyberfriends at T 1 lowered social anxiety at T 2; opposite effect for the High attractive group This result obtained for same sex cyberfriends only Path F was not significant This kind of data is hard to punctuatethere Is always a T 0 beforehand that has not been measured

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups For the low attractiveness group, lots of cyber-friends at T 1 reduced the loneliness felt in friendships but not in family relationships or society For the high attractiveness group, large number of cyber-friends at T 1 increased the loneliness felt in society but not in friendships or family relationships

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • The presence of same sex cyberfriends seemed to have an anxiety lowering effect • This may because the “true” self is less likely to emerge when there is a sexual or romantic possibility to the friendship • Found no significant causal relationship between social anxiety at T 1 and the number of subsequent cyberfriends, and it didn’t matter if they evaluated their attractiveness as high or low • Having a large number of cyberfriends was associated with more loneliness in the family, which may mean that the subject was spending more time online and less time with family members

Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences Ando & Sakamoto (2007), The effect of cyber-friends on loneliness and social anxiety: Differences between high and low self-evaluated physical attractiveness groups • For the attractive group, there were no positive effects of having a large number of online friends • Spiral process-the higher loneliness is, the more interacting with cyberfriends will reduce that loneliness • Another type of spiral process- the more loneliness you feel in society, the more you interact with cyberfriends, but then interacting more with cyberfriends makes you feel more lonely with friends and family, so you reduce the amount of time you spend with friends online in favor of f 2 f with friends and family

IMing, text messaging, and adolescent social networks • Young people are using these technologies IMing, text messaging, and adolescent social networks • Young people are using these technologies to maintain social contact and make plans with family and friends in addition to their f 2 f talks • IMing and text messaging easier and in some countries cheaper than traditional technologies, and the synchronous aspect is also attractive. • However, when the topic is important or requires in-depth interaction, they still talk f 2 f

IMing, text messaging, and adolescent social networks • Authors suggest that network analysis hasn’t IMing, text messaging, and adolescent social networks • Authors suggest that network analysis hasn’t been used much in studying adolescent online social networks and it can be useful in understanding such things as the dynamics of an entire network or the characteristics of subsets of the network such as the “popular kids” • Also needs to be more research on the social uses of text messaging; 64% of teens with mobile phones used it in 2005 • 65% of American teens were reported in 2005 to be using IM

IMing, text messaging, and adolescent social networks From Lenhart, A. Madden, M. Rankin Macgill, IMing, text messaging, and adolescent social networks From Lenhart, A. Madden, M. Rankin Macgill, A. Smith, A. , Teens and Social Media: The use of social media gains a greater foothold in teen life as email continues to lose its luster. Washington, DC: Pew Internet & American Life Project, December 19, 2007.

IMing, text messaging, and adolescent social networks • • Teens are more likely to IMing, text messaging, and adolescent social networks • • Teens are more likely to agree that the internet helps to maintain existing relationships than to agree that it helps to make new friends Ito and Daisuke, however, argue that teens through using these technologies are substituting lesser relationships for stronger ones by spending more time connecting with weak ties Chan and Cheng found that online initiated relationships had less depth at least in the early stages, although this became more equal with relationship length Authors bring up weak ties, bridging capital as possible ways to characterize what adolescents are getting out of these social technologies, hence – “ RQ 1. Are adolescents creating more, but weaker, ties using SITs? ” – After some very convoluted and unconvincing discussion, the authors proposed a second research question: – “RQ 2: To what extent do adolescent SIT communication networks overlap with their friendship networks? ” and – “RQ 3: Are SIT-based relationships important for adolescents who have fewer offline peer ties? “

IMing, text messaging, and adolescent social networks • • • Method – collected data IMing, text messaging, and adolescent social networks • • • Method – collected data from 7 th graders in a single midwestern college town- survey data on their use of IM and text messaging “For the open-ended friendship network questions, the participants were asked to list up to 25 people and then to identify those people as "close friends, " "good friends, " or just "friends. " “ “For the IM and text message networks, they were asked to list up to 25 people with whom they communicate using each of these technologies and then to differentiate among those people with whom they communicated "most often, " "often, " or "occasionally. " “ “Finally, the questionnaire asked the participants how they view these SITs as fitting within the social and emotional spheres of their daily life. ” “The questionnaires thus yielded three types of data: 1) a set of three selfreport ego-networks (peer, IM, and text message networks) for each participant, 2) self-report data regarding media usage and adoption that was used as attribute data for each of the participants (or nodes in the networks), and 3) self-report data regarding feelings of social isolation/belonging and social support. ””

IMing, text messaging, and adolescent social networks • Results: – What the participants did IMing, text messaging, and adolescent social networks • Results: – What the participants did on IM • • Keep in touch with friends 92. 0% Make plans with friends 88. 0% Play games with IM software 61. 5% Play a trick on someone 60. 0% Ask someone out 44. 0% Write something you wouldn't say in person 42. 0% Send non-text information 38. 5% Break up with someone 24. 0%

IMing, text messaging, and adolescent social networks • Study participants spent 2. 2 hours IMing, text messaging, and adolescent social networks • Study participants spent 2. 2 hours per day IMing but only 2. 82 hours per week on text messaging • Most participants indicated that they had a lot of friends (average more than 17), maybe half a dozen close friends, and kept up with them by phone, email and chat rooms, in that order, other than IM or text messaging • 15. 2% said that they had more than 80 IM partners

IMing, text messaging, and adolescent social networks • Answering RQ 1. Are adolescents creating IMing, text messaging, and adolescent social networks • Answering RQ 1. Are adolescents creating more, but weaker, ties using SITs? Answer, NO actually fewer but no less intense – significant difference between total number of friends listed and total number of IM partners – significant difference between total number of friends listed and total number of text messaging partners – number of friends was greater than the number of SIT-based relationships. – no significant difference between total number of IM and text messaging partners. – Re strength of ties, relationship intensity was average of the number of close friends (or communicated with most frequently via IM or text messaging), divided by the total number of friends – “no significant difference in relational intensity between friendship networks and text messaging networks, between friendship networks and IM partner networks, or between IM partner networks and text messaging networks”

IMing, text messaging, and adolescent social networks • Results, cont’d • “RQ 2: To IMing, text messaging, and adolescent social networks • Results, cont’d • “RQ 2: To what extent do adolescent SITfacilitated networks overlap with their friendship networks? ” • analyzed each participant's valued ego-networks using quadratic assignment procedure (QAP) correlation analysis. • “Overall, there was little correlation between the dichotomized friendship network and the 2 SIT networks. Only nine significant relationships were found across 23 participants who use IM and have friendship networks”

IMing, text messaging, and adolescent social networks • A second analysis of the network IMing, text messaging, and adolescent social networks • A second analysis of the network data looked at intensity of the relationship • little correlation between the intensity of the online and offline relationships • “RQ 3: Are online relationships important for adolescents who have fewer offline peer ties? ” • People with comparatively fewer friends had markedly lower rate of using IM and about the same rate of text messaging as people with more friends • Didn’t seem to be an alternative source of friends for people with few in their offline network • It was unlikely that subjects would have the same friends online as offline, based on results obtained in this study. Their time online may be more spent talking to acquaintances.

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs • Strong evidence that people use the Internet to fulfill social and interpersonal goals • Blogs are being used for this purpose along with email and social networking sites, IM, video sharing, and other applications • Blogs are popular in part because they are easy to start and maintain • Most people who maintain blogs make them available to the public rather than just friends or family

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs • Authors are interested in the extent to which individual personality characteristics influence the breadth and depth of a blogger’s social networks, and how these network features influence the use and adoption of blogs as tools of relationship maintenance • Authors see blogs as another instantiation of the appropriation of new communications technologies for use in formation and maintenance of social relations, regardless of purposes for which the technology was originally envisioned

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs • Herring et al found that about 70% of blogs could be classified as personal journals • Niardi et al found that bloggers fully expect to receive feedback on their posts, and through a variety of channels including f 2 f • Bloggers have been found to present personal and intimate information in their blogs and to have an intended audience in mind of family and friends

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs • Authors believe that personality traits, especially extraversion (warmth, activeness, gregariousness, broad range of relationships) and disclosiveness, may be important variables predicting blogging activity – What is a trait? Stable, global predisposition to behave in a certain way across a variety of contexts and situations – Sometimes also called a disposition – Most current thinking about traits (and in some quarters thinking about traits is regarded as old-fashioned) focuses on the Big Five traits (openness to experience (intellectualsim), conscientiousness, extraversion, agreeableness, neuroticism) • There has not been much research connecting traits to blog writing characteristics – One study found a relationship between agreeableness and a more formal writing style

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs • Authors propose that a combination of extraversion and disclosiveness result in a motivation to maintain large networks of strong ties, and that this then predicts to likelihood of using blogs for relational maintenance – (would also be interesting to study blog reading and posting (e. g. audience activity) as a behavior motivated by the same goal) • Extraversion as a trait has to do with the issue of extent or breadth of social networks • Self-disclosure has to do with depth of relationships – Reciprocity effects in self-disclosure encourage deeper relationship formation • Hypothesis: “There is a positive relationship between the combination of extraversion and self-disclosure traits and strong tie network size. “ (see model next slide)

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs Are their some additional elements that could have been included in this model, such as perceived usefulness, ease of use, self-as-source affordances, subjective norm, attitude toward blogging, motivation for use? Should they be? Motivation to maintain ties is an implicit causal variable but is not explicitly measured. Is presence of large strong tie networks a mediator in this model? Not treated as such in the analysis although the discussion tends to treat it that way

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs • In ego-centric social networks, a “node’s” social ties may be characterized as weak or strong ties – Strong tie contacts: stable, frequent, reciprocal communication usually over a long period of time- typically, family and intimate friends – Weak ties could display less frequent communication, less reciprocity, and less intimate bonding, although some weak ties related to work or task may have frequent, long-term, highly reciprocal contact as well • One of the key indicators would be the nature of the reciprocity-in long-term intimate relationships it may not be immediate, as in exchange relationships, but may be worked out over time because there is an expectation that the relationship will continue – We don’t usually get that kind of info in social network data

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs • Since strong ties require more time to maintain, as the size of these increase so too should the motivation to use mediated maintenance techniques like SNS or blogs • Thus, “H 2: Strong tie social network size is positively related to use of blogs for relationship maintenance. ” • Bloggers who target largely friends and family have been shown to post more information to their blogs which will reveal personal identity • Thus, “ H 3: People who report being easily identified by the content of their blog use their blogs to maintain existing relationships”

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs • Method • Using a random blog generator on blogger. com, generated a list of 1000 blogs – 700 remained after excluding blogs that were all pictures, had multiple authors, commerical intent, from minors, not in English, and other exclusion criteria – 622 surveys were sent out to those remaining bloggers who provided email addresses – Response rate was 24. 7%, 154 completed surveys

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs • Using a small number of items for each construct, the survey asked bloggers to self-report on their – extraversion, – identifiability in the blog, – self-disclosiveness (Note this is NOT a measure from content analysis of their actual blog posts-in fact they were asked to imagine this in the context of f 2 f with friends) – a single item measure of strong tie size (how many close friends do you have? ) – reciprocal use (with friends and family) of the blog for relational maintenance purposes (talking about the blog, posting to the blog by friends and family)

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs • Results confirmed the hypotheses – Extraversion was significantly related to selfdisclosure and strong tie network size – Use of blogs for relationship maintenance was significantly related to both identifiability and strong tie network size Combo of high disclosure and high extraversion dramatically increases number of strong ties

Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: Stefanone, M. A. , & Jang, C. -Y. (2007). Writing for friends and family: The interpersonal nature of blogs • “The identifiability variable was included in the second block and was a significant predictor of the relationship maintenance function (final β=. 239), accounting for 7. 2% of the variance explained” – Odd way to put it-not vary likely that blog identifiability explains motivation to maintain relationships

More data about authoring (e. g. blogs and other self-as-source media) from Pew Internet More data about authoring (e. g. blogs and other self-as-source media) from Pew Internet report • Data from Pew report suggests that people are now coming of age expecting to use online authoring applications for self-expression and maintenance of personal relationships – “ 64% of online teens ages 12 -17 have participated in one or more among a wide range of content-creating activities on the internet, up from 57% of online teens in a similar survey at the end of 2004. – 39% of online teens share their own artistic creations online, such as artwork, photos, stories, or videos, up from 33% in 2004. – 33% create or work on webpages or blogs for others, including those for groups they belong to, friends, or school assignments, basically unchanged from 2004 (32%). – 28% have created their own online journal or blog, up from 19% in 2004. – 27% maintain their own personal webpage, up from 22% in 2004. – 26% remix content they find online into their own creations, up from 19% in 2004. ”

More data about authoring (e. g. blogs and other selfas-source media) from Pew Internet More data about authoring (e. g. blogs and other selfas-source media) from Pew Internet report, con’td

Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and offline social relationships among adolescents in Israel. • Homophily (the state of being similar to one another) is a known correlate of friendship formation • Homophily is rewarding because two people who are similar not only validate each others’ views and tastes but may also enjoy common activities together • Homophily is likely a combination of two factors, proximity and shared social status • When adolescent friendships are studied only in the school context, it is difficult to disentangle the effects of proximity and similarity

Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and offline social relationships among adolescents in Israel. • Many adolescent friendships are formed online although they may move quickly to f 2 f • Online context may promote self-disclosure in circumstances of comparative anonymity and in the absence of the usual cues to physical appearance or other potentially handicapping qualities • The authors state that there don’t seem to be any studies comparing the qualities of online and offline friendships – The authors need to look harder! (e. g. Chan and Cheng study)

Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and offline social relationships among adolescents in Israel. • Authors look at adolescent online and offline friendships in various contexts and look at the extent to which friends’ similarity is related to the quality of friendships that originated online, at school, and in their neighborhoods • Method – Started with a sample of 1000 households in Israel; ended with 987 agreeing to participate – Selected neighborhoods within settlements at random and depending on the number of teens in the settlement selected more or fewer neighborhoods within that settlement, then randomly selected 15 households within the neighborhoods – Conducted interviews in the family home – A typical interviewee was a 15 year old from a still-intact Jewish family where the parents’ education was secondary school – They were most likely to have met their friends at school, then in the neighborhood, then online (only 11%) – Those with online friends were on average a few months younger

Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and offline social relationships among adolescents in Israel. • Friends’ similarity (the respondents similarity to the first friend they named) was measured with dummy variables indicated whether they lived in proximity or not, were of similar age within one year or not, and were of the same gender or not • Subjects were also asked to rate the strength of their ties to the first named friend, the place where they first met (neightborhood, school, online) • Also reported the number of hours they spent online, and whether or not their activities were mostly for social or for instrumental purposes • A measure of respondent self-esteem was administered

Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and offline social relationships among adolescents in Israel. • Similarity was higher among friends who first met f 2 f than online, although similarity among online friends was still pretty high • The difference was particularly marked for age similarity, which was 80. 4% for f 2 f and only 42. 4% for online first meeting friends • Some other findings • Living in the same place as friends was associated with lower SES (mother’s education), and presumably less mobility in terms of personal transportation • Making friends with opposite sex members was related to age (older > more opposite sex friends) • Greater gender heterogeneity was associated with online friends • In general, making friends outside of school decreased homophily with respect to age and gender and with respect to residence as well when the friend was met online

Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and Mesch, G. , & Talmud, I. (2007). Similarity and the quality of online and offline social relationships among adolescents in Israel. • Weaker ties were more characteristic of friends who had been met online as opposed to those who had been met at school • Interestingly, friends who met in the neighborhood had stronger ties than school-met In the second model an interactive term was introduced, and the result • It was found that ties were stronger for online friendships if the pair had residential similarity • Gender similarity increased the strength of ties to friends met online • Having siblings seemed to decrease the strength of friendship ties