Exploring Social Media as a Socioeconomic Mobility Tool for the Homeless

Yinuo Han, Eri Phinisee, Darren Mok
Human-Computer Interaction Institute, Carnegie Mellon University
05899: Social Data Science
Professor Hirokazu Shirado
Dec 8, 2021


Information communication technology (ICT) access is an established priority for the homeless. Past research shows its importance in alleviating the burden of homelessness. ICT is used by the homeless to maintain connections with family and friends, manage self presentations, and access critical support infrastructures as well as employment resources (Eyrich-Garg, 2010; Sala & Mignone, 2014; Le Dantec, 2008). Access to social support in particular has been demonstrated to improve behavioral, physical, and mental health outcomes (Hwang et al., 2009; Sala & Mignone, 2014). More broadly, ICT is an essential link to modern society, welcoming the homeless into the digital world already inhabited, experienced, and cultivated by the general population (Le Dantec, 2008).

Given this, the natural question is how this disadvantaged population can improve their situation through ICT use. The use of social media particularly interested us as “the possession of and ready access to an online identity… is becoming increasingly necessary for finding services, jobs, and managing personal connections” (Le Dantec, 2008) and yet past research only investigated the relationship between a homeless person’s social media use and behaviors such as substance use and risky sexual behaviors (Rice, 2010; Rice et al., 2010; Rice et al., 2010). Therefore, we sought to address the gap in knowledge from both ends by investigating how social media uses lead to socioeconomic improvement.

We developed four hypotheses: First, active usage of social media improves one’s socioeconomic status more than passive usage because it is linked to greater social capital and well-being (Burke et al., 2010); Second, having more connections on social media improves one’s socioeconomic status more due to greater access to social support and chances to gain useful information; Third, an online network with less constraint improves one’s socioeconomic status more because connections from diverse groups serve as unique sources of information (Burt, 1994); Finally, using social media to seek financial help is more helpful to improving socioeconomic status than seeking emotional and informational help based on the reasoning that financial resources are the most direct and versatile source of economic power.

Economic inequality is severe in the United States (Fig. 1), with the bottom 50% sharing a miniscule portion of the overall wealth (Clemens, 2019). The poorest sector, i.e., the homeless are competing for extremely scarce resources while having little access to any resources. The outcome of our research is beneficial for such community as changing the way one uses social media comes at no cost.

 Figure 1 

Preparations and Ethical Considerations

We identified multiple preparatory steps with ethical considerations. First, we would reach out to homelessness non-governmental organizations (NGOs) for collaboration. An NGO partner could help with participant-recruitment, and be of valuable ethical guidance. We have already contacted several NGOs in Ann Arbor and San Francisco (with prior knowledge regarding homelessness in these cities) to introduce them to our proposal and ask for evaluations. We got all confirmatory responses, insights will be included in the following paragraphs discussing specific preparatory steps.

In recruiting participants, our NGO partner could help us reach the first potential participants and retain stable connections with them. To reach more participants who are not affiliated with the NGO, we will perform a snowball sampling method: asking recruited participants to help recruit more individuals, giving compensation for such help. To ethically confirm this method, we gained approvaltory advice from an experienced social worker, and consulted identical studies regarding the homeless population, finding similar use of this method (Eyrich-Garg, 2010).

After recruition, we will do pre-study interviews to screen participants and establish baselines. Information from these interviews can be split into background information and previous social media use. Background information includes age, gender, current living condition, duration of homelessness, etc. These help us screen suitable participants and establish socioeconomic baselines. Previous social media use, including possession of ICT devices, past experiences with social media, etc., helps establish social media usage baselines. In terms of ethics, we researched similar studies, and saw some training interviewers prior to interviewing vulnerable groups (Rice et al., 2010). We will ask our NGO partner to provide subsequent training, and ask for a social worker to be present at interviews.

The last preparatory step is to ask participants to sign consent forms, providing an overview of the study, benefits and risks involved, confidentiality of private information, and acknowledgement of the ability to withdraw. We also hope to provide support from social workers throughout the study. We will let participants choose between getting a new phone, or having the bills for their original phone (if possessed) paid as compensation.


The study utilizes a two-step approach with an in-depth longitudinal study and a confirmatory mass survey. In the longitudinal study, we will ask participants to complete mobile surveys every three months over five years. This longitudinal approach is chosen because socioeconomic status usually takes extended time to change (Nobles, Weintraub, and Adler, 2013).

The mobile surveys include different kinds of questions targeting our four hypotheses. First, we propose utilizing a scale to measure active and passive social media usage (Li, 2016). We define active usage as actions such as commenting and sharing, while passive usage are behaviors such as viewing content. In questions regarding active and passive usage, response options “never”, ‘‘once a week”, …, ‘‘several times a day” will be provided. Responses will be quantized to analyze results. Secondly, to investigate our hypothesis regarding the number of connections, we will ask participants to report their number of connections with screenshots, as a simple way to verify reported results. We would also ask participants to self-report estimations of overlappings, and take overlappings into account in evaluations. Thirdly, to address the constraint hypothesis, we will utilize Burt’s measure of constraint (Burt, 1994). We will ask participants to list up to five online connections they had the most interaction with over the past month, and indicate if a connection knows another with “1” or “0”, (“1” meaning two connections know each other, “0” meaning the opposite). A numerical value could be calculated as a representation of a participant’s constraint. Fourthly, we will investigate how objectives on social media impact outcomes. Previous research suggests asking questions such as "which platform do you use the most" and "what motivation do you have for using social media" with response options as an efficient measure (Brandtzæg, Heim, 2009). To increase accuracy, we will ask participants to provide screenshots accordingly at times.

We will measure participants’ socioeconomic status with both subjective and objective questions. An example for a subjective question is the IFLS subjective socioeconomic status indicator, in which participants are asked to place themselves on a 6-rung ladder where 1 represents the poorest and 6 represents the richest (Nobles, Weintraub, and Adler, 2013). Objective questions will target information regarding employment, income, housing,  etc.

A nationwide mass survey on Amazon Mechanical Turk (AMT) will be performed after the longitudinal study, focusing on respondents below the poverty line. This survey is on how social media have impacted one’s socioeconomic status, with questions adapted from the longitudinal study. As we have no access to respondents’ previous lives, we acknowledge the inability to confirm self-reported results. We will, however, ask respondents to report accurately. The data collected from these mass surveys could help synthesize findings from the longitudinal study and broaden results to a national level.


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Violet Han @2023