Community, Group and Individual: A Framework for Designing Community Technologies

Sheena L. Erete1

1. Assistant Professor, College of Computing and Digital Media, DePaul University in Chicago, IL, USA. E-mail:


Education, crime, and environmental conditions are just a few of the concerns that communities face (Green, 1979). It is important for the wellbeing of local residents that such social issues are addressed (Guite, Clark, & Ackrill, 2006). Traditional community interventions - petitions to government officials, neighborhood watches, and local cleanups - require that community members meet in person to participate. Yet as technology becomes pervasive, people are considering the use of community technologies to support local engagement. Many community technologies, however, are unsuccessful due to a lack of sustained participation from community members (Foth, Gonzalez, & Kraemer, 2008). Although there is a growing body of literature in the human computer interaction (HCI) field that focuses on community technologies (Carroll, 2001; Gurstein, 2000; Schuler, 1994), few studies discuss how to design community technologies that are intended to solve local problems. Thus, I pose the research question: What factors should be considered when designing effective community technologies?

In this paper, I present a theoretical framework consisting of three components: community, group, and individual. By asking the question, "How does a community technology engage communities/groups/individuals?," we can begin designing more effective community technologies. Each of the three components of the proposed framework has related dimensions. Community is influenced by the amount of support the technology provides to increase social cohesion and social capital. Group engagement relates to the size of the group that the technology aims to engage - small or large. The number of topics a community technology focuses on (i.e., many topics or one specific topic) affects individual engagement. Using this framework, I discuss past community technologies and present three best practices when designing community technologies: 1) increase social cohesion and social capital, 2) engage small groups of community members, and 3) encourage participation through interest-based technologies. Using a hypothetical community technology, I illustrate how each of these design factors can be incorporated into the development of new technologies.

The next section provides a brief overview of the framework, while subsequent sections discuss each component of the framework in detail, including theory, examples, and design implications.


The fields of HCI and community informatics (CI) have been at the forefront of proposing theoretical framing for community technologies. Gurstein (2000) provided insight into how communities used technologies to participate in local democratic processes in the late 1990s and predicted the potential impact that technology could have on communities in the future. Although this book provides a foundation for understanding community technologies, it does not account for the growth and transformations that have occurred over the past decade and a half (e.g., the prominence of social media). Other studies in CI also provide theoretical frameworks. Arnold and Stillman (2013), for example, describe how the field of CI theorizes social power and the impact it has on collective agency. Thakur (2009) proposed an analytic framework that focuses on how community groups participate in the democratic process and used it to evaluate a governance program in Jamaica. Both of these frameworks are essential to understanding how ICTs affect the relationship between local communities and other entities (e.g., government agencies); however, neither focuses on how to design effective technologies for local communities. This paper proposes that social and economic contexts, the extent and nature of participation, the scope and purpose of ICTs, and institutional balance are essential to understanding community participation in the democratic process.

There are other studies that describe the use of community technologies (Carroll, 2001; Foth, et al., 2008), but few describe factors that should be considered when designing effective technologies for geographically-bound communities. Based on sociological and urban studies literature (Dewey, 1927; Forrest & Kearns, 2001; Johnson, 1973), I propose three components that should be considered when designing technologies for geographically-bound communities: community, group, and individual (see Figure 1). Each component of the framework has relative dimensions (see Figure 2).

Figure 1: Illustration of Community Technologies Framework
figure 1
Figure 2: List of dimensions that relate to each of the three components of the framework.
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Understanding the community in which the community technology is to be situated is critical to its success. A common method of assessing community is by considering the relationships amongst community members, or cohesiveness (Forrest & Kearns, 2001). Additionally, researchers measure the number of resources that emerge as a result of connections between community members (Putnam, 2001). The two methods mentioned above - social cohesion and social capital, respectively - are standard techniques for understanding community connectedness (Kawachi et al., 1997; Pigg & Crank, 2004). The proposed framework suggests that designers should consider how community technology supports social cohesion and social capital within a community.

The second component of the framework focuses on how the technology engages groups of people. Traditional community interventions tend to engage either large or small groups (Brudney, 1990). Group size is directly related to the amount of participation in traditional community interventions (Levy, et al., 1972). Therefore, when designing community technologies that are intended to support (or even replace) traditional community interventions, user adoption of the community technology may be affected by the size of the group the technology engages. Thus, group engagement is an important factor to consider when designing community technologies.

People participate in community activities because they are interested in a specific issue (e.g., community beautification) (Anderson & Moore, 1978; Schindler-Rainman & Lippitt, 1971). A person's motivation for participating may stem from a number of reasons including, but not limited to, personal experience, religion, value systems, and community wellbeing. Despite the motivation, the issue is important to the individual. Therefore, the third component of the framework focuses on how the technologies engage individuals. Technologies support either one specific topic (e.g., crime) or many community topics (e.g., crime, health, homelessness). We refer to these as interest-based or non interest-based technologies. It is vital that we understand how community technologies engage individuals.

Figure 3 illustrates each of the components of the framework along with their dimensions on a continuum. Community technologies support either high or low social cohesion and social capital, engage small or large groups of people, and address either interest or non-interest based topics. In this paper, I argue best practices for creating community technologies that are intended to act as interventions. Specifically, community technologies should support high social cohesion and social capital, engage small groups, and focus on one specific topic (see box in upper left of Figure 3).

Figure 3: Framework on 3-D Axes
figure 3

The proposed framework can be applied to new and existing community-based technologies. Appendix A provides a comprehensive list of existing community-based technologies evaluated by the framework. The following section describes a hypothetical community-based technology that will be referenced throughout this paper to illustrate the three components of the framework.

R U OK?: An Illustration

Although there are many issues that communities must address, crime is a major issue that influences physical safety and emotional wellbeing (Guite, et al., 2006). Numerous community technologies have been created to address local crime (Blom, et al., 2010; Blythe, Wright, & Monk, 2004); however, few have been successful. Throughout the paper, I describe a hypothetical community technology that illustrates the three design implications that emerged from applying the framework.

R U OK? is an SMS-based community technology that distributes real-time information about the safety of community members during the event of a violent crime (e.g., a gang shoot-out) in areas that experience excessive amounts of crime (Lewis, 2010). It provides an opportunity for people to connect and check on each other during emergency situations. To begin, users sign up at a local organization (e.g., church, community center, library) using their cell phone numbers. They are initially placed into groups of four or five people based on the characteristics of the people with whom they would like to interact. For instance, a single mother may want to connect with other single mothers. Likewise, college students from out-of-town may want to be placed in the same safety group. Once enrolled, users have the option to connect with their safety group members offline or online. They could arrange to meet in-person (if they do not already know them) or add them to their social networking application(s) (e.g., Facebook, LinkedIn) to interact further.

There are two ways that messages are distributed. First, messages are sent through the automated system that is connected to the local police department. This allows people to receive real time information about violent crimes. Second, community members can initiate alerts inquiring about the safety of those in their group and send messages to each other about precautions they may need to take because of local crime and disorder. For example, a concerned parent may send a message saying, "Gangs hanging out near the elementary school today. Kids walking home from school should be careful."

Text messages from R U OK? inquire about users' safety and provide information about crimes that occur near one's home or job. An example of a message would be, "Are you okay?" After five minutes or if everyone in the safety group responds, another message would say, "A robbery occurred on 3rd and Madison. Everyone in your group has responded that they are okay. Reply YES if you would like to receive additional updates about this incident."

I will refer back to R U OK? to illustrate how design implications drawn from the theoretical framework can be incorporated into the design of a community technology. The next section describes the first component of the framework - community.


Building social cohesion and social capital are vital to the success of local communities (Forrest & Kearns, 2001; Wellman & Wortley, 1990) and both should be considered when designing community-based technologies. Social cohesion is the degree of social bonding, or the amount of trust, hope, group identity, and sense of belonging (Berkman & Kawachi, 2000). Social cohesion has been considered a major method for studying community because it measures closeness and shared values amongst community members. Community cohesion leads to increased engagement in activities that support the collective good (Forrest & Kearns, 2001; Woolley, 1998). In her book, Mapping Social Cohesion: The State of Canadian Research, Jane Jenson (1998) describes five dimensions to measure social cohesion:

  1. belonging <---> isolation
  2. inclusion <---> exclusion
  3. participation <---> non-involvement
  4. recognition <---> rejection
  5. legitimacy <---> illegitimacy

In addition to social cohesion, another vital element of a successful community is social capital. Social capital refers to resources that are available through social connections. Robert Putnam (2000) defines social capital as "features of social organization, such as trust, norms, and networks, that can improve the efficiency of society by facilitating coordinated actions." He further describes his take on social capital.

"The central idea of social capital is that networks and the associated norms of reciprocity have value. They have value for the people who are in them, and they have demonstrable externalities, so that there are both public and private faces of social capital. Accepting that there is no single form of social capital, we need to think about its multiple dimensions" (Putnam, 2001).

These dimensions include levels of trust, perceived reciprocity, extent of obligation, participation, empowerment, and collective norms/values (Forrest & Kearns, 2001).

The major difference is that social cohesion is the connectedness and solidarity of a group, while social capital describes the resources that are available to group members (Berkman & Kawachi, 2000). Elements of social capital have been used to evaluate social cohesion; therefore, some consider social cohesion a subset of social capital (Ibid: 2000).

Community technologies should be designed to increase both social cohesion and social capital amongst community members. Communities that have high social cohesion are more engaged in addressing public concerns (e.g., hazardous waste and crime) than those that do not (Forrest & Kearns, 2001). High social capital has been linked to more effective functioning local governing bodies, an increased economic growth rate, and less crime (Hirschfield & Bowers, 1997). Members of communities with high social cohesion and social capital are happier and healthier than those in communities with low social cohesion and social capital (Coburn, 2000; Putnam, 2001). Considering the importance of factors such as engagement and effective governing, it is essential that when creating community technologies, we consider designs that are aimed at increasing social cohesion and social capital.

Social Cohesion and Social Capital in Community Technologies

Technologies have been created that support community social cohesion or social capital; however, few technologies consider the importance of designing for both. Those that do design for both social cohesion and social capital have slightly more success; yet, they lack other elements (i.e., considering the importance of group and individual engagement - described further in this paper), which are vital for successful community technology. This section evaluates community technologies based on how they support social cohesion and social capital.

Some technologies focus on social cohesion, but not on social capital. For example, in an effort to increase sense of belonging (Jenson, 1998), an element of social cohesion, Resnick and Shah (2002) created a shared photo album to improve face recognition amongst community members. This is an example of a technology that intends to increase social cohesion but not social capital, because there are no definite social connections made that provide access to resources. Similarly, Familiar Stranger is a wearable device that keeps track of strangers that people habitually encounter but do not know personally (Paulos & Goodman, 2004). The device alerts users when they encounter other residents that they have been in close physical proximity to in the past (e.g., a user at the grocery store would be alerted if they encountered someone who was on their morning commuter train). This is another example of a technology that intends to support social cohesion through recognition, but not social capital.

The drawback to designing technology that supports only social cohesion is that the direct benefit of using the tool is unclear; thus, use of the technology rapidly decreases. In both of the community technology examples mentioned above, participants experienced increased recognition of other community members and feelings of belonging, which strengthens social cohesion; however, participants did not use the tools beyond the study (some stopped before the study ended), because the tool did not provide a direct advantage - such as increased resources. By designing tools that increase social capital, community members will benefit from using the tool; therefore, cases where users disengage because they feel the purpose of using the technology is vague will be reduced.

There are clear benefits to designing tools that support social capital. One main benefit is that community members will have access to more social resources through the connections that are made. For example, EatWell empowers community members by providing an opportunity to share stories about their healthy eating habits through asynchronous voice recordings (Grimes, Bednar, Bolter, & Grinter, 2008). While EatWell is designed to build social capital through empowerment (Forrest & Kearns, 2001) by allowing community members to share recipes and locations to buy healthy food, it does not support social cohesion or bonding, because the entries are anonymous. Le Dantec's Community Resource Map (CRM) is another example of a mobile technology designed to increase social capital amongst homeless community members by supplying information about employment, food, and shelters gathered from local community organizations and other people who are homeless (Le Dantec, 2010). This system supports social capital, because people rely on others to obtain resources. Yet because people do not directly engage with each other, recognition (Jenson, 1998) - an element of social cohesion - is not established.

Lack of contribution is the major weakness that emerges from designing systems that support only social capital and not social cohesion. People receive information but rarely provide information because the social bonds that encourage reciprocity are not built. Both EatWell and the CRM report few contributors during the study, which eventually leads to stale, irrelevant information. Since there is less of a perceived need to contribute, there is a lack of participation. However, designing opportunities for cohesion or bonding encourages people to contribute, because they feel they belong and that their contribution adds value.

Additionally, there have been a few community technologies designed to increase both social cohesion and social capital; however, these tools lack other design elements that are discussed further in this paper. For example, Hampton's (2010) i-Neighbors is an online website that allows community members to retrieve information about local events (e.g., concerts, plays) as well as critical local issues, such as crime and legislature. This tool provides people with a way to discuss common goals, increase solidarity about issues, and even increase attachment to the neighborhood (physical place), all measures of social cohesion. For example, one neighbor reported on the website that youth were throwing trash in an elderly lady's yard and declared that no one will be allowed to destroy their neighborhood. Rallying around this declaration, residents organized a beautification day to address the trash that was thrown and to improve the general appearance of the neighborhood. Residents later commented that they were pleased with the event participation and results. They also said that they enjoyed interacting with their neighbors. This illustrates how technology can increase commitment to physical place and solidarity amongst community members. Furthermore,'s messaging feature allowed social connections to be made, where people become information resources. Similarly, Carroll, Rossen, and colleagues (1999) created Blacksburg Nostalgia, a technology that allowed the elderly to create an oral history of Blacksburg, VA. Users said that knowing the history of the community increased feelings of closeness to other residents. While the original intent was to store historical information about the community (social capital), Blacksburg Nostalgia also fostered social cohesion. Although both of these technologies increase social capital and social cohesion, they lack other design considerations such as interest-based participation, which is vital to create technology that sustains engagement.

Table 1: Summary of results based on community technologies' support of social cohesion and social capital
table 1

Technologies that focus only on social cohesion and not on social capital increase the sense of community and closeness over time; however, the use of these technologies are short lived because residents discontinue use when they do not see a direct benefit. On the other hand, technologies that increase social capital provide connections to resources, which is a clear benefit of use. However without social cohesion, contribution is low because of the lack of social bonds that lead to feelings of reciprocity, which increase the likelihood of one contributing. People who do not feel a bond or closeness with other residents are less likely to feel reciprocity or a need to contribute (Gouldner, 1960). Thus, only a few contributors remain and, eventually, the information becomes stale and usage declines. While there are some community technologies that support both social cohesion and social capital, most do not consider other factors that make successful community building technology, such as the importance of engaging small groups or focusing on one topic.

R U OK?: Designing Social Cohesion and Social Capital

Understanding how to engage community is the first component in the framework to design and evaluate community technology. In the preceding sections, I presented theory regarding the importance of social cohesion and social capital in communities and examined how past community technologies have (or have not) supported social cohesion and social capital in their design. To explore methods of designing community technologies that support high social cohesion and social capital, I refer back to R U OK? , the hypothetical community technology introduced earlier in this paper. Recall that R U OK? allows small groups of community members to interact via text message about safety in their neighborhoods. Consider the following scenario:

Don is a graduate student who has lived in the Edgewood community his entire life without incident, despite the high crime rate; however, he recently became the victim of a robbery when walking home from school. Like many victims, he becomes nervous while in his neighborhood so he decides to join an R U OK? safety group and requests to be connected to others who have been victimized. After connecting with his new safety group via Facebook, Don and his group decide to: 1) sync their schedules so that at least two people can walk from the train station to their respective homes together when arriving after dark (as they typically arrive around the same time) and 2) they decide to have monthly meetings at local coffee shops regarding their experiences of being victims as a way to begin the healing process. In addition to receiving information about local crimes in his area, Don's perceptions of safety and community increase due to his interaction with a group of people who have had experiences similar to his own.

The example above describes how R U OK? facilitates the connecting of group members through bonding and recognition. Specifically, during signup, users of R U OK? are connected with people who have certain characteristics that are important to them. In the scenario above, the user decided to connect with other community members who had had similar experiences (i.e., all had been victims), and they were able to bond over these experiences by starting a support group. Through the connections made by R U OK? , community members were able to begin to identify each other (recognition) and unite as a result of their similar characteristics. Additionally, R U OK? supports social capital as illustrated in the example above. Users received information relative to their location and they were able to form a "buddy-system," when walking home at night from the train. These resources stem from the social connections that are supported by the R U OK? system.

This section provides theory about the importance of social cohesion and social capital to communities. Successful community technologies consider methods to support and increase social cohesion, or closeness, amongst community members and social capital by allowing them to utilize each other and information from the system as resources. The following section describes theory, examples, and design implications of the second component in the proposed framework - group.


People are most willing to participate in local community activities when they feel a sense of belonging and obligation, which originates from having personal connections to other community members (Kerr, 1983). These personal connections provide people with the feeling that their individual contributions are important and recognized by others in the community (e.g., "I'm not just a number. Sam and Donna appreciate my time."). Personal recognition of an individual's contribution leads to increased participation over time (Gidron, 1985). Furthermore, group size inversely predicts the likelihood of volunteerism (Levy, et al., 1972).

"In some situations, notably in 'large groups,' any individual's contribution is too small to make a noticeable difference in the level of the collective good, so everyone's contribution is irrational no matter what anyone else does. But in 'small groups' such as the active members of a community organization, individual contributions do make a noticeable difference and predictions about others' behavior are relevant. People who believe others will provide the collective good are motivated to ride free; people who do not believe others will provide the collective good are motivated to provide the good themselves..." (Oliver, 1984).

This predicts that community interventions that engage large groups without personalized interactions have less sustained participation than those organized into small groups, because the anonymity of large groups discourages helping behavior (Diener, 1980; Schwartz & Fleishman, 1978; Solomon, Solomon, & Stone, 1978). For instance, large volunteer organizations that do not separate their volunteers into small groups have low retention rates, because those who volunteer in large groups feel that their contribution does not matter (Gidron, 1985; Olson, 1971). Therefore, to improve participation in community activities, engaging small groups, where people communicate and work closely with four to seven others, is ideal (Oliver, 1984).

In addition to increased engagement, people are likely to adhere to social norms if they feel as though they are a part of a group (Zimbardo, 1969). Volunteers in small groups abide by norms of community engagement such as consistent and meaningful participation in order to maintain their reputation amongst those who know them (Milinski, Semmann, & Krambeck, 2002; Sugden, 1984). Furthermore, trust is more prominent in small groups than large groups (Sato, 1988). Thus, many community activities are based inside of pre-established organizations such as local churches, schools, etc. Residents identify with these organizations and their leaders as pillars in the community and are hesitant to trust new unfamiliar organizations. Engaging small groups provides the opportunity to interact with others who are familiar, as opposed to strangers in a large group. Small group engagement leads to high retention rates, reciprocity, and trust.

Lastly, people are less likely to participate in community activities if too much time is demanded (Foth, 2006). Thus, groups that are too small (less than three members) are less likely to be successful because the workload is placed on too few individuals.

The Effect of Group Size on Community Technology Adoption

Community technologies designed to engage large groups receive participation from a small number of community members that dominate the tool. Foth (2006) designed a community technology that was created to facilitate discussion amongst residents of three different urban apartment complexes in Australia. Over time, a small percentage of residents began to dominate the community message board, which led others in the community to lose interest and abandon the system or simply lurk (Foth, 2006; Preece, Nonnecke & Andrews, 2004). This happens frequently to systems that are built for large groups (Takahashi, Fujimoto & Yamasaki, 2003). By designing technologies that aim to engage small groups (four to seven people), there is a lesser chance of one or two people dominating the interaction and alienating others, because there is increased accountability amongst small group members (Festinger & Thibaut, 1951; Kerr, 1983).

Another issue regarding systems designed for large groups is adherence to social norms, which impacts the need for censorship of information. For example, researchers created an authoring system that supports public discourse amongst local community members by taking pictures and writing captions (Ananny, Biddick & Strohecker, 2003). The pictures and captions were posted for everyone to view; however, users complained that censorship was needed because people would post irrelevant information. In technologies that support large groups, people are more likely to post information that is inappropriate because they are not closely connected with other group members. Members of small groups, however, feel more of an obligation to adhere to social norms (Zimbardo, 1969), which will limit the circulation of inappropriate information.

People may hesitate using information from technology built to support large groups, because they do not know the other users that are providing the information. For example, users of ComfortZone (Blom, et al., 2010), a system that allows people to annotate a virtual map based on how safe they feel, did not trust the information that was provided by other users. They wanted to know more about the users who posted information so they could better assess their background. In this example, people wanted more background on other members of the organization, which they felt would help them trust the information. Similarly, users of MapMover, an interactive system that allows people to share kinetic and audio expressions of the city that is displayed on a large-scale public map, did not interact with other community members' information, because they did not know or trust the source (DiSalvo, Maki & Martin, 2007). These examples demonstrate the importance of trust in community technologies, which is easier to establish when engaging small groups (Sato, 1988).

Technology built for large groups limits the amount that individuals are willing to contribute, because there is less of a sense of reciprocity. Users may feel that information provided through the community technology was created for their use and that their input or participation is not needed. This increases the potential for lurkers who do not provide content which, in turn, increases the likelihood that the technology will fail (Nonnecke & Preece, 2000; Preece, et al., 2004). For instance, the Speakeasy system, an integrated web and telephone service that provides local residents with free translation services, relied purely on altruism for participation from multi-lingual volunteers (Hirsch & Liu, 2004). Alhough the system was not tested over an extended period of time, researchers expressed concern about the drop-off rate of volunteers. Participation is a large concern, especially for systems designed to engage large groups, because there is less incentive for users to give back. Technologies that support small groups, however, provide an incentive for contributing because being in a small group induces feelings of reciprocity. Also, small groups alleviate the pressure of working in pairs, which requires that one person constantly contribute, as demonstrated in Speakeasy.

I propose that we leverage the characteristics of small groups (four to seven people) in order to increase engagement and sense of community. Designing technologies that engage small groups will increase awareness because people will be more likely to regard information provided by those in their small group.

R U OK?: Engaging Small Groups

Engaging groups is the second component of the framework for designing community technologies. As stated above, the size of the group is key and the examples above reveal issues that arise when community technologies are created for large groups (i.e., lack of contribution and trust). Technologies created for pairs of users (two people), on the other hand, may warrant too much pressure and time for users to contribute. Hence, designing community technologies for small groups (four to seven people) is a better solution. R U OK? , for example, connects groups of four or five people and provides the safety status of each group member. Therefore, users are less likely to become overwhelmed with information, and the safety group is small enough that they can have a personal interaction with each other. Consequently, group members may feel an increased sense of community. Below is an example scenario of how the use of small groups can improve the success of a community technology:

Sue, a member of an R U OK? safety group, is a new resident in a high crime neighborhood. On the bus headed home from work, she receives an alert that local gangs are shooting near her home. She responds that she is okay and receives notice that the other three women in her group are also okay. Being new to the area, she asks others for suggestions of a place she could wait for a few hours. Sarah, a member of Sue's group, suggests that Sue accompany her to an evening church service, which is on Sue's bus route, until things subside. Not only has Sue avoided possible danger, but also, being a member of a small group, she is able to bond with a community member and explore a new church.

By creating technologies that utilize small groups of people, users may become highly engaged because of personal connections. They are likely to feel a greater connection to group members without feeling the heavy pressure from the dependence that may occur by being in a smaller group (e.g., two people). Small group engagement would not require that group members allocate large amounts of time. Instead, these small groups would focus only on issues that are of interest to group members. The next section discusses theory, examples, and design implications for the third and final component of the framework - individual.


Community engagement increases when community activities are constructed around preexisting social conditions that are unique to a place (e.g., violence in Chicago), because people are intrinsically motivated to participate in activities that have personal significance (Dewey, 1927). For instance, people may be more likely to attend a town hall meeting to support or oppose a position of personal concern than a general town hall meeting. An individual who states, "I want to stop gang violence in my community" is more likely to be consistently involved in community improvement activities for longer than someone who states, "I want to help my community." The former has a specific goal or target for helping the community (i.e., decreasing gang violence), while the latter statement is a general statement. Community organizations that target a specific topic have higher retention rates than those that do not (Smith, 1975). While residents with general goals may participate in various communal efforts, a person who is passionate about a specific topic is more likely to take part in community activities for a longer period of time (Johnson, 1973).

The Role of Interests in Community Technologies

Technologies that focus on a specific topic, or interest-based technologies, allow people to rally around an issue of personal importance (e.g., health, crime, education). It is essential that community technologies are designed to support specific (as opposed to general) content because those who unite to address topics that are commonly important are likely to participate intently (Smith, 1975; Unger, 1991). Interest-based tools are customized to address a specific topic, while non interest-based technologies do not. Non interest-based technologies provide users with many topic options. The amount of topics, however, can be overwhelming and much of the information becomes outdated because only a few people continue to contribute or "dominate" the tool. The scenario below illustrates problems with non interest-based technologies:

Maya, a local resident, is seeking information about safety on a non interest-based system. She searches through material about education, neighborhood events, government information, etc., which are section titles created by other users. There is information on a safety seminar in the neighborhood but Maya does not see it because it is in the community events section, not the safety section. Maya becomes frustrated believing that there is no relevant information on safety so she does not use the system in the future to find information on safety.

Non interest-based technologies rely on people categorizing and tagging information for group understanding. This can be problematic because it is based on personal interpretation (Rader & Wash, 2008), which can result in online information that is difficult for others to find (as exhibited in the above scenario). Thus, people may be less likely to use non interest-based technologies, because the information can be overwhelming and disorganized.

Communities are less likely to adopt technologies that are not created for a specific topic. For example, Hampton's i-Neighbors system (2007) allowed local residents to have online discussions about any topic such as crime, beautification projects, local daycares, and local government issues. Similarly, Blacksburg Nostalgia (Carroll, et al., 1999) provided community members with information about events occurring in Blacksburg, Virginia. Both of these community-building technologies did not focus on specific interests or topics but instead, allowed local residents to post information that they thought was relevant. Residents were given the opportunity to address a plethora of topics, which causes confusion and a lack of clarity of purpose. Both authors report a significant decline in usage after the study ended, and that users were unsure where to look for information, as there were many different topics.

Interest-based technologies connect people and facilitate discussion surrounding one topic. For instance, EatWell, a system that focuses on health, aims to improve the eating habits of an Atlanta community by allowing people to share recipes. Similarly, safety is the focus of ComfortZone, a mobile phone system that allows residents to denote areas where they feel unsafe on a virtual map (Blom, et al., 2010). Both EatWell and ComfortZone focus on a specific topic within a local community - i.e., health and safety, respectively. Users of both systems stated that they were excited to use the tools because they were interested in health or personal safety. These systems provide an opportunity for users to explore topics in which they are intrinsically motivated to engage. The major weakness of the two examples above is that they do not attempt to facilitate social cohesion, another consideration vital to the success of community technologies; therefore, users did not feel they needed to contribute because of a lack of reciprocity. Successful community technologies should: design for social cohesion and social capital, engage small groups, and focus on specific interests. Although a community technology may address one of the three components of the framework presented in this paper, without addressing the others, the technology's chance of success diminishes.

R U OK?: Designing Interest-based Community Technologies

The third and final component of the proposed framework is considering how to engage individuals. As mentioned above, the topic(s) that the community technology address(es) are important when engaging an individual. R U OK? is an example of a community technology designed to address one topic, safety. Community members are alerted of local crimes that occur and are provided with the status of people within their safety group. By providing information to people that is focused, residents who are interested in safety will be able to use the system without being distracted or annoyed with information that is irrelevant to their concerns. This may in fact limit the amount of users but there are other systems that could provide additional information to people, if they are concerned about other topics (e.g., health, education). By creating technologies that are specific, people are able to focus on information that they find significant, without encountering information that they do not.

In this section, I define interest and non-interest based technologies. I propose the design of community-based technologies that focus on a particular interest. Community technologies should address one specific topic rather than general topics. Interest-based technologies have a higher chance of being adopted and used over a period of time because there is a personal interest in using the system. Interest-based technologies allow people to rally around one issue they care about. Thus, they will be more passionate about engaging and less annoyed with receiving information that they are not interested in.


The objective of this paper is to inform the design of community technologies. Drawing upon sociological and urban studies literature, I present a conceptual framework that focuses on the need to improve community, group, and individual engagement. The dimensions associated with the three concepts in the framework are social cohesion/capital, group size and interests, respectively. Using this framework, I recommend three best practices vital when designing community technologies. We should design to: 1) increase social cohesion and social capital, 2) engage small groups of community members, and 3) encourage participation through interest-based technologies. These considerations have the ability to foster personal relationships amongst community members that encourage participation in local initiatives. Designing interest-based community technologies that increase social cohesion and social capital through small group interaction leads to greater engagement amongst communities. Although R U OK? illustrates the components of the framework, future work should test the validity and scalability of the proposed framework. Whether the goal of a community technology is to improve health or reduce crime, this framework helps researchers and practitioners design technological interventions that are more likely to be adopted by local community members, thereby improving its chances of success.


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