Offline Social Relationships and Online Cancer Communication: Effects of Social and Family Support on Online Social Network Building

Breast cancer survivorship needs: a qualitative study

BACKGROUND

Breast cancer rates and the number of breast cancer survivors have been increasing among women in Iran. Effective responses from healthcare depend on appropriately identifying survivors' needs. This study investigated the experience and needs of breast cancer survivors in different dimensions.

METHODS

In this qualitative content analysis, semi-structured in-depth interviews were conducted from April 2023 to July 2023. Data saturation was achieved after interviewing 16 breast cancer survivors (BCSs) and four oncologists using purposive sampling. Survivors were asked to narrate their experiences about their needs during the survivorship. Data were analyzed with an inductive approach in order to extract the themes.

RESULTS

Twenty interviews were conducted. The analysis focused on four central themes: (1) financial toxicity (healthcare costs, unplanned retirement, and insurance coverage of services); (2) family support (emotional support, Physical support); (3) informational needs (management of side effects, management of uncertainty, and balanced diet); and (4) psychological and physical issues (pain, fatigue, hot flashes, and fear of cancer recurrence).

CONCLUSIONS

This study provides valuable information for designing survivorship care plans. Identifying the survivorship needs of breast cancer survivors is the first and most important step, leading to optimal healthcare delivery and improving quality of life. It is recommended to check the financial capability of patients and take necessary measures for patients with financial problems. Additionally, support sources should be assessed and appropriate. Psychological interventions should be considered for patients without a support source. Consultation groups can be used to meet the information needs of patients. For patients with physical problems, self-care recommendations may also be useful in addition to doctors' orders.

Using Machine Learning of Online Expression to Explain Recovery Trajectories: Content Analytic Approach to Studying a Substance Use Disorder Forum

BACKGROUND

Smartphone-based apps are increasingly used to prevent relapse among those with substance use disorders (SUDs). These systems collect a wealth of data from participants, including the content of messages exchanged in peer-to-peer support forums. How individuals self-disclose and exchange social support in these forums may provide insight into their recovery course, but a manual review of a large corpus of text by human coders is inefficient.

OBJECTIVE

The study sought to evaluate the feasibility of applying supervised machine learning (ML) to perform large-scale content analysis of an online peer-to-peer discussion forum. Machine-coded data were also used to understand how communication styles relate to writers' substance use and well-being outcomes.

METHODS

Data were collected from a smartphone app that connects patients with SUDs to online peer support via a discussion forum. Overall, 268 adult patients with SUD diagnoses were recruited from 3 federally qualified health centers in the United States beginning in 2014. Two waves of survey data were collected to measure demographic characteristics and study outcomes: at baseline (before accessing the app) and after 6 months of using the app. Messages were downloaded from the peer-to-peer forum and subjected to manual content analysis. These data were used to train supervised ML algorithms using features extracted from the Linguistic Inquiry and Word Count (LIWC) system to automatically identify the types of expression relevant to peer-to-peer support. Regression analyses examined how each expression type was associated with recovery outcomes.

RESULTS

Our manual content analysis identified 7 expression types relevant to the recovery process (emotional support, informational support, negative affect, change talk, insightful disclosure, gratitude, and universality disclosure). Over 6 months of app use, 86.2% (231/268) of participants posted on the app's support forum. Of these participants, 93.5% (216/231) posted at least 1 message in the content categories of interest, generating 10,503 messages. Supervised ML algorithms were trained on the hand-coded data, achieving F1-scores ranging from 0.57 to 0.85. Regression analyses revealed that a greater proportion of the messages giving emotional support to peers was related to reduced substance use. For self-disclosure, a greater proportion of the messages expressing universality was related to improved quality of life, whereas a greater proportion of the negative affect expressions was negatively related to quality of life and mood.

CONCLUSIONS

This study highlights a method of natural language processing with potential to provide real-time insights into peer-to-peer communication dynamics. First, we found that our ML approach allowed for large-scale content coding while retaining moderate-to-high levels of accuracy. Second, individuals' expression styles were associated with recovery outcomes. The expression types of emotional support, universality disclosure, and negative affect were significantly related to recovery outcomes, and attending to these dynamics may be important for appropriate intervention.

A comparison of the sociodemographic, medical, and psychosocial characteristics of adolescents and young adults diagnosed with cancer recruited in-person and online: A Canadian cross-sectional survey

Introduction

Adolescents and young adults diagnosed with cancer (AYAs) are under-represented in research. The Internet and social media could increase the reach of recruitment efforts but may impact sample characteristics. This study evaluated the characteristics of AYAs recruited in-person at an urban hospital versus the Internet in terms of their sociodemographic and medical characteristics, and psychosocial wellbeing, and offers recommendation for increasing the inclusivity and representativeness of research samples.

Methods

Participant data from a cross-sectional survey of AYAs in Canada were evaluated. In-person hospital recruitment used a registry to identify patients attending ambulatory clinics. Internet recruitment included notices on hospital, team members', and community partners' social media channels, and email newsletters. Independent sample t-tests and Chi-squared tests were used to identify differences in participant sociodemographic, medical, and psychosocial characteristics based on recruitment source.

Results

Of 436 participants, 217 (49.8%) were recruited in-person and 219 (50.2%) online. Online participants were more likely: to be white (p < .001), women (p < .001), and Canadian-born (p < .001); to speak English at home (p < .001), live alone (p = .001) and live in rural settings (p = .014); and to be farther from diagnosis (p = .023), diagnosed with breast cancer (p < .001), and cancer free (p < .001) compared to the hospital sample. Online participants also reported higher anxiety, depression, and loneliness (p < .001), and lower social support (p < .001), self-efficacy for coping with cancer (p < .001), and life satisfaction (p = .006).

Conclusions

Online recruitment yielded a more geographically diverse but less sociodemographically diverse sample of AYAs who were farther from diagnosis and had poorer psychosocial wellbeing than in-person recruitment at an urban hospital. Future research efforts should consider partnering with under-represented communities and using targeted and stratified online and in-person recruitment strategies to achieve an inclusive and representative sample of AYAs.

Leveraging digital technology for social connectedness among adults with chronic conditions: A systematic review

Purpose

To review the evidence about the impact of digital technology on social connectedness among adults with one or more chronic health conditions.

Methods

PubMed, Embase, Social Sciences, CINAHL, and Compendex were systematically searched for full-text, peer-reviewed empirical evidence published between 2012 and 2023 and reported using the PRISMA flow diagram. Articles were critically appraised applying the Joanna Briggs Institute checklists. Specific data were extracted based on the framework for social identity and technology approaches for health outcomes and then analyzed and synthesized.

Results

Thirty-four studies met study criteria. Evidence showed heterogeneity among research methodology, chronic health conditions, digital technology, and health outcomes. Technology use was influenced by factors such as usability, anonymity, availability, and control. More advanced digital technologies require higher digital literacy and improved accessibility features/modifications. Social support was the most measured aspect of social connectedness. The emotional and informational forms of social support were most reported; instrumental support was the least likely to be delivered. Self-efficacy for using technology was considered in seven articles. Sixteen articles reported health outcomes: 31.2% (n = 5) described mental health outcomes only, 18.8% (n = 3) reported physical health outcomes only, 31.2% (n = 5) detailed both physical and mental health outcomes, whereas 18.8% (n = 3) denoted well-being or quality-of-life outcomes. Most often, health outcomes were positive, with negative outcomes for selected groups also noted.

Conclusion

Leveraging digital technology to promote social connectedness has the potential to affect positive health outcomes. Further research is needed to better understand the social integration of technology among populations with different contexts and chronic health conditions to enhance and tailor digital interventions.

Social Enhancement and Compensation in Online Social Support among Cancer Patients: The Role of Social Network Properties

Although several researchers have reported evidence that the benefits of Internet use depend on users' offline resources, the factors responsible for this phenomenon are not well understood. We examined a network-based explanation for social enhancement (i.e., rich get richer) and social compensation (i.e., poor get richer) in the context of received social support among adults coping with cancer. After first controlling for support received offline, we tested the role of two offline network properties in predicting support received online. The results were mostly consistent with social enhancement. Offline group affiliation was associated with greater levels of support received online. Additionally, significant indirect effects were observed from offline group affiliation to support received online through online group affiliation as well as from offline tie strength to support received online through online tie strength.

Intraindividual, Dyadic, and Network Communication in a Digital Health Intervention: Distinguishing Message Exposure from Message Production

Communicating within digital health interventions involves a range of behaviors that may contribute to the management of chronic illnesses in different ways. This study examines whether communication within a smartphone-based application for addiction recovery produces distinct effects depending on 1) the "level" of communication, defined as intraindividual communication (e.g., journal entries to oneself); dyadic communication (e.g., private messaging to other individuals); or network communication (e.g., discussion forum posts to all group members), and 2) whether individuals produce or are exposed to messages. We operationalize these communication levels and behaviors based on system use logs as the number of clicks dedicated to each activity and assess how each category of system use relates to changes in group bonding and substance use after 6 months with the mobile intervention. Our findings show that (1) intraindividual exposure to one's own past posts marginally predicts decreased drug use; (2) dyadic production predicts greater perceived bonding; while dyadic exposure marginally predicts reduced drug use; (3) network production predicts decreased risky drinking. Implications for digital health interventions are discussed.

Breast cancer patient experiences through a journey map: A qualitative study

BACKGROUND

Breast cancer is one of the most prevalent diseases in women. Prevention and treatments have lowered mortality; nevertheless, the impact of the diagnosis and treatment continue to impact all aspects of patients' lives (physical, emotional, cognitive, social, and spiritual).

OBJECTIVE

This study seeks to explore the experiences of the different stages women with breast cancer go through by means of a patient journey.

METHODS

This is a qualitative study in which 21 women with breast cancer or survivors were interviewed. Participants were recruited at 9 large hospitals in Spain and intentional sampling methods were applied. Data were collected using a semi-structured interview that was elaborated with the help of medical oncologists, nurses, and psycho-oncologists. Data were processed by adopting a thematic analysis approach.

RESULTS

The diagnosis and treatment of breast cancer entails a radical change in patients' day-to-day that linger in the mid-term. Seven stages have been defined that correspond to the different medical processes: diagnosis/unmasking stage, surgery/cleaning out, chemotherapy/loss of identity, radiotherapy/transition to normality, follow-up care/the "new" day-to-day, relapse/starting over, and metastatic/time-limited chronic breast cancer. The most relevant aspects of each are highlighted, as are the various cross-sectional aspects that manifest throughout the entire patient journey.

CONCLUSIONS

Comprehending patients' experiences in depth facilitates the detection of situations of risk and helps to identify key moments when more precise information should be offered. Similarly, preparing the women for the process they must confront and for the sequelae of medical treatments would contribute to decreasing their uncertainty and concern, and to improving their quality-of-life.

Online Support Seeking and Breast Cancer Patients: Changes in Support Seeking Behavior following Diagnosis and Transition off Cancer Therapy

Transitions in breast cancer care are associated with significant increases in stress and anxiety, and this stress can negatively impact mental and physical health. Social support has been shown to alleviate such distress, but whether, how, and how often social support is accessed through existing support networks is unclear. Our study examines changes in social media use following breast cancer diagnosis and treatment, using hand-coded longitudinal data from 30 breast cancer survivors' Facebook pages for the 6 months surrounding cancer diagnosis and for the 6 months surrounding transition off cancer therapy. Results revealed that following diagnosis, there was a significant increase in posting behavior and self-disclosure. However, this increase in posts did not correspond to an increase in support requests. In addition, while participants' primary support requests were for resources, support provided tended to be lower-cost emotional support. Finally, temporal maps indicated that participants started off increasing their engagement but withdrew over time. Our findings suggest that Facebook offered participants a platform for continued social engagement and self-disclosure - but showed several indications that support was principally low-effort, limited quality, and ill-fitting.

How Cancer Patients Benefit from Support Networks Offline and Online: Extending the Model of Structural-to-Functional Support

Although social support is an indispensable resource for coping with illness, the connections among the structural properties of one's support network, received social support from offline and online network members, and well-being are not well understood. This study aims to extend the model of structural-to-functional support by distinguishing offline from online support networks and identifying different pathways through which these two networks contribute to patients' emotional well-being. Using data from 386 cancer patients, the results revealed that offline and online support networks were associated with patients' emotional well-being via different types of received support. Specifically, offline support network size was negatively associated with their emotional well-being via informational support received offline. Online support network size was positively associated with their emotional well-being via emotional support received online.

Effects of Web-Based Social Connectedness on Older Adults' Depressive Symptoms: A Two-Wave Cross-Lagged Panel Study

Background

Depressive symptoms are the most prevalent mental health concern among older adults (possibly heightened during the COVID-19 pandemic), which raises questions about how such symptoms can be lowered in this population. Existing research shows that offline social connectedness is a protective factor against depression in older adults; however, it is unknown whether web-based social connectedness can have similar effects.

Objective

This study investigates whether social connectedness on a support website protects older adults against depressive symptoms over the course of a year, above and beyond the protective effect of offline social connectedness. The secondary aim is to determine whether older adults with increased depressive symptoms are more likely to engage in social connectedness on this website. Thus, we examine depressive symptoms as both an outcome and predictor of web-based social connectedness to fully understand the chain of causality among these variables. Finally, we compare web-based social connectedness with offline social connectedness in their ability to lower depressive symptoms among older adults.

Methods

A total of 197 adults aged 65 years or older were given access to a social support website, where they were able to communicate with each other via a discussion forum for a year. Participants’ social connectedness on the web-based platform, conceptualized as message production and consumption, was measured using behavioral log data as the number of messages participants wrote and read, respectively, during the first 6 months (t₁) and the following 6 months (t₂) of the study. Participants self-reported their offline social connectedness as the number of people in their support networks, and they reported their depressive symptoms using the Patient Health Questionnaire-8 both at baseline (t₁) and at 12-month follow-up (t₂). To ascertain the flow of causality between these variables, we employed a cross-lagged panel design, in which all variables were measured at t₁ and t₂.

Results

After controlling for the effect of offline support networks at t₁, web-based message consumption at t₁ decreased older adults’ depressive symptoms at t₂ (β=−.11; P=.02), but web-based message production at t₁ did not impact t₂ depressive symptoms (β=.12; P=.34). Web-based message consumption had a larger effect (β=−.11; P=.02) than offline support networks (β=−.08; P=.03) in reducing older adults’ depressive symptoms over time. Higher baseline depressive symptoms did not predict increased web-based message consumption (β=.12; P=.36) or production (β=.02; P=.43) over time.

Conclusions

The more messages older adults read on the web-based forum for the first 6 months of the study, the less depressed they felt at the 1-year follow-up, above and beyond the availability of offline support networks at baseline. This pinpoints the substantial potential of web-based communication to combat depressive symptoms in this vulnerable population.

International Registered Report Identifier (IRRID)

RR2-10.1186/s13063-015-0713-2

Online social support among breast cancer patients: longitudinal changes to Facebook use following breast cancer diagnosis and transition off therapy

PURPOSE

Active social engagement, both on and offline, is widely recognized as an important buffer against the negative effects of cancer-related stress. Nevertheless, studies show that social stigma can lead to a decrease in available social support following cancer diagnosis. This study examines whether Facebook friends provide continuous, health-promoting social support to breast cancer patients following transitions in care.

METHODS

To examine support provided to breast cancer patients, we hand-coded 21,291 status updates and wall posts with respect to both post content and support exchange. We then use descriptive statistics, pairwise t tests, and temporal maps to show whether posts received more likes, comments, or unique commenters following breast cancer diagnosis and the post content that was most likely to garner positive responses from Facebook friends.

RESULTS

Results showed an initial increase across all three support metrics (likes, comments, and unique commenters) after cancer diagnosis but that all three metrics decrease steadily over time. Results also revealed significant decreases in the average number of comments and number of commenters following transition off cancer treatment.

CONCLUSIONS

Taken together, our results reveal that while support is available through Facebook, support may be sporadic, characterized by limited engagement and low cost. There is also limited support available through Facebook to weather the stress of transition off cancer treatment.

IMPLICATIONS FOR CANCER SURVIVORS

Facebook is an important feature in people's lives, particularly among the demographic most impacted by breast cancer. Our results suggest that social media can be useful in accessing support but should be used with caution.

Investigating relationships among cancer survivors' engagement in an online support community, social support perceptions, well-being, and moderating effects of existing (offline) social support

PURPOSE

Socially supportive relationships help cancer survivors cope with their diagnosis and may improve quality of life; however, many survivors report unmet support and information needs. Online communities of survivors may address these needs, but research on their benefits have been equivocal. This cross-sectional, self-report study investigated relationships among cancer survivors' level of engagement in an online survivor community (The American Cancer Society Cancer Survivors Network®; CSN), perceptions of emotional/informational support available from online communities ("online social support"), well-being, and moderating effects of "offline social support."

METHODS

Participants were 1255 registered users of the CSN who completed surveys between 2013 and 2014. Three types of engagement with the CSN-social/communal, interpersonal communication, and informational/search engagement-were identified through principal components analysis. Regression analyses examined hypotheses.

RESULTS

More frequent social/communal and interpersonal communication engagement were associated with increased online social support (p < .0001), and the relationship between interpersonal communication engagement and online social support was strongest for survivors reporting lower offline social support (interaction β = - .35, p < .001). Greater online social support was associated with increased well-being, but only among survivors reporting low offline social support (interaction β = - .35, p < .0001).

CONCLUSIONS

Engagement in online survivor communities may increase support perceptions that promote well-being, but benefits may accrue more to survivors reporting low offline social support.

IMPLICATIONS FOR CANCER SURVIVORS

Newly diagnosed cancer survivors, particularly those with unmet emotional/informational support needs, should be given the opportunity to communicate with other survivors through online survivor support networks.

Codifying Online Social Support for Breast Cancer Patients: Retrospective Qualitative Assessment

BACKGROUND

Social media has emerged as the epicenter for exchanging health-related information, resources, and emotional support. However, despite recognized benefits of social media for advancing health-promoting support exchange, researchers have struggled to differentiate between the different ways social support occurs and is expressed through social media.

OBJECTIVE

The objective of this study was to develop a fuller understanding of social support exchange by examining the ways in which breast cancer patients discuss their health needs and reach out for support on Facebook and to develop a coding schema that can be useful to other social media researchers.

METHODS

We conducted a retrospective qualitative assessment of text-based social support exchanges through Facebook among 30 breast cancer survivors. Facebook wall data were systematically scraped, organized, coded, and characterized by whether and which types of support were exchanged. Research questions focused on how often participants posted related to cancer, how often cancer patients reached out for support, and the relative frequency of informational, instrumental, or socioemotional support requests broadcast by patients on the site.

RESULTS

A novel ground-up coding schema applied to unwieldy Facebook data successfully identified social support exchange in two critical transitions in cancer treatment: diagnosis and transition off cancer therapy. Explanatory coding, design, and analysis processes led to a novel coding schema informed by 100,000 lines of data, an a priori literature review, and observed online social support exchanges. A final coding schema permits a compelling analysis of support exchange as a type of peer community, where members act proactively to buffer stress effects associated with negative health experiences. The coding schema framed operational definitions of what support meant and the forms each type of support could take in social media spaces.

CONCLUSIONS

Given the importance of social media in social interaction, support exchange, and health promotion, our findings provide insight and clarity for researchers into the different forms informational, resource, and emotional support may take in Web-based social environments. Findings support broader continuity for evaluating computer-mediated support exchange.

The Influence of Marital Status on Contemporary Patterns of Postmastectomy Breast Reconstruction

BACKGROUND

Marital status is known to influence quality of life, survival, and treatment decision-making after breast cancer diagnosis. We aimed to determine whether relationship status impacts contemporary patterns of immediate breast reconstruction.

METHODS

Surveillance, Epidemiology, and End Results (SEER)-18 was used to identify females undergoing mastectomy for stage 0-III breast cancer from 1998 to 2014. Multivariate logistic regression was used to estimate the association of relationship status with the likelihood of postmastectomy reconstruction. Patients were grouped by diagnosis year to assess change in the reconstructed population with time. Among younger patients ≤45 years, a generalized logistic model was used to predict reconstruction subtype.

RESULTS

Among 346,418 patients, reconstruction after mastectomy was more likely to occur in women with relationship support in the form of a marriage or partner [odds ratio (OR) 1.31; 95% confidence interval (CI), 1.28-1.34; p<0.001]. Women who were separated (OR 0.76), single (OR 0.73), or widowed (OR 0.56) were significantly less likely than married women to undergo reconstruction (all p<0.001). During the 17-year study period, change in reconstruction rates with time varied by relationship status (interaction p=0.02), with reconstruction rates among divorced patients increasing more slowly than those among married and partnered women. Among younger women, subtype patterns varied by relationship status (p=0.004), with divorced women less likely to receive autologous over implant reconstruction (OR 0.87; p = 0.03).

CONCLUSION

Relationship status may influence decision-making regarding pursuit and type of postmastectomy reconstruction. Consideration of support networks of patients with breast cancer could facilitate tailored preoperative counseling by reconstructive surgeons.

Social Media Campaign Effects: Moderating Role of Social Capital in an Anti-Smoking Campaign

This study examined the effects of an anti-smoking campaign that employs a crowdsourcing method with a social networking service. Drawing upon social capital scholarship and the expression effect research paradigm in eHealth systems, the study also investigated the roles of social trust and community life satisfaction in the social media campaign that has a specific geographical boundary. To that end, we conducted an experiment using a two-group pretest-posttest design. We randomly assigned 201 participants to two conditions: "campaign message reception only" as a control group and "message reception and expression" as a treatment group in which participants fully engaged in the campaign process by sharing their own campaign ideas with other participants. Findings revealed that social trust and community life satisfaction interacted with the treatment condition to positively affect persuasive intentions, but in distinct ways. Social trust moderated the effect of the message reception and interaction condition on participants' willingness to encourage community members to stop smoking. In contrast, community life satisfaction moderated the effect of the treatment condition on encouraging others to comply with the community's anti-smoking policy. These results provide theoretical and practical implications related to the roles of social capital in geographically defined social media campaigns.

Harnessing Facebook for Smoking Reduction and Cessation Interventions: Facebook User Engagement and Social Support Predict Smoking Reduction

Background

Social media technologies offer a novel opportunity for scalable health interventions that can facilitate user engagement and social support, which in turn may reinforce positive processes for behavior change.

Objective

By using principles from health communication and social support literature, we implemented a Facebook group–based intervention that targeted smoking reduction and cessation. This study hypothesized that participants’ engagement with and perceived social support from our Facebook group intervention would predict smoking reduction.

Methods

We recruited 16 regular smokers who live in the United States and who were motivated in quitting smoking at screening. We promoted message exposure as well as engagement and social support systems throughout the intervention. For message exposure, we posted prevalidated, antismoking messages (such as national antismoking campaigns) on our smoking reduction and cessation Facebook group. For engagement and social support systems, we delivered a high degree of engagement and social support systems during the second and third week of the intervention and a low degree of engagement and social support systems during the first and fourth week. A total of six surveys were conducted via Amazon Mechanical Turk (MTurk) at baseline on a weekly basis and at a 2-week follow-up.

Results

Of the total 16 participants, most were female (n=13, 81%), white (n=15, 94%), and between 25 and 50 years of age (mean 34.75, SD 8.15). There was no study attrition throughout the 6-time-point baseline, weekly, and follow-up surveys. We generated Facebook engagement and social support composite scores (mean 19.19, SD 24.35) by combining the number of likes each participant received and the number of comments or wall posts each participant posted on our smoking reduction and cessation Facebook group during the intervention period. The primary outcome was smoking reduction in the past 7 days measured at baseline and at the two-week follow-up. Compared with the baseline, participants reported smoking an average of 60.56 fewer cigarettes per week (SD 38.83) at the follow-up, and 4 participants out of 16 (25%) reported 7-day point prevalence smoking abstinence at the follow-up. Adjusted linear regression models revealed that a one-unit increase in the Facebook engagement and social support composite scores predicted a 0.56-unit decrease in cigarettes smoked per week (standard error =.24, P=.04, 95% CI 0.024-1.09) when baseline readiness to quit, gender, and baseline smoking status were controlled (F_{4, 11}=8.85, P=.002).

Conclusions

This study is the first Facebook group–based intervention that systemically implemented health communication strategies and engagement and social support systems to promote smoking reduction and cessation. Our findings imply that receiving one like or posting on the Facebook-based intervention platform predicted smoking approximately one less cigarette in the past 7 days, and that interventions should facilitate user interactions to foster user engagement and social support.

Expression and Reception: An Analytic Method for Assessing Message Production and Consumption in CMC

This article presents an innovative methodology to study computer-mediated communication (CMC), which allows analysis of the multi-layered effects of online expression and reception. The methodology is demonstrated by combining the following three data sets collected from a widely tested eHealth system, the Comprehensive Health Enhancement Support System (CHESS): 1) a flexible and precise computer-aided content analysis; 2) a record of individual message posting and reading; and 3) longitudinal survey data. Further, this article discusses how the resulting data can be applied to online social network analysis and demonstrates how to construct two distinct types of online social networks - open and targeted communication networks - for different types of content embedded in social networks.