Not particularly proud of this post but here goes:
It’s Not Just Who You Know, It’s Who You Are: Individual Difference on Network Structuring
Several theories have been proposed to explain the spread of information and behaviors via social networks. Contagion theory seeks to explain the dissemination of information, messages, attitudes and beliefs by applying a biological metaphor to social networks (Contractor and Monge, 2002). Its primary tenant is that mere exposure to different ideas, attitudes and behaviors can bring about a change in the previously existing ideas, attitudes and behaviors (Monge & Contractor, 2003). While this may be a necessary condition to provoke change, it certainly is not a sufficient condition. Rather, the spread of ideas is likely contingent upon attributes of individual network nodes, the structure of the existing network, as well as cognitive evaluations of messages by their recipients.
The theory of homophily holds that individuals tend to develop networks of others like themselves which are based on social categories developed from key social dimensions such as age, gender, race, professional afflictions and other demographic characteristics. In short, “birds of a feather flock together”. Which demographic characteristics are salient for the formation of a social identity is a result current situational demands and the networks structure (Monge and Contractor, 2003). One of the major implications of contagion theory is that people who are in regular contact will have similar attitudes, beliefs, and ideas. This line of reasoning suggests that contagion theory contributes to the creation of a group culture among relatively homogenous individuals who are in frequent contact. However, even among relatively homogenous groups differences between individual nodes may inhibit the transmission of ideas and beliefs.
The principle of homophily suggest that external similarities between network nodes lead to the creation of networks between similar individuals. However, when networks are created online in the absence of individuating information, external traits of nodes may be reduced in their importance (Postmes & Baym, 2005). Rather, individuals who identify with one another online may fall back on social identities created from similar attitudes or interests. As a result, online homophily has the potential to enhance the contagious spread of ideas and beliefs. Social identities have the potential to influence an individual’s thoughts and actions as a result of self-categorization and social identification. These processes may lead to group norms and values being internalized. Therefore, information that is salient to the social identity of an online group may be more likely to be disseminated within the group via a contagion model and subsequently retained and internalized among group members than the same information among individuated offline groups.
Contagion theory suggests a centralized distribution pattern of information around key nodes with the infected nodes radiating outwards. Proximal nodes are more likely to be exposed than nodes that are further away. Proximity increases the potential that individuals have contact and learn from one another (Monge & Contractor, 2003). The potential to develop communicative links among nodes decreases drastically with the increase of distance. Likewise the theory of electronic proximity suggests that far-flung ties resulting from new media would free information from it’s geographically based dispersal pattern. However, research has indicated that some technologies, such AOL instant messenger, are used as often to talk to individuals who are geographically proximal as to individuals geographically distant. Furthermore, the primary use of email has been found to be scheduling face-to-face meetings (Contractor, Lecture). Therefore, it is reasonable to assume that while new media may provide a mechanism for the distribution of ideas and beliefs, information dispersal will still consist of a tight geographically collocated cluster with much looser halo of “infected” nodes as geographical distance increases. This pattern is representative of a small world network and can provide insight into the spread of ideas and attitudes through a network. Small world networks can be defined as those “where nodes have a high degree of local clustering with a small fraction of nodes (that is, these nodes are interconnected to one another), while at the same time being no more than a few degrees of separation from all of the remaining nodes” (Monge & Contractor, 2003). Small world networks have a few connections to other distant nodes which serve as short cuts for information spreading across a network.
The contagion theory assumes that mere exposure is sufficient to spread information and beliefs. However, message reception by human nodes should be considered from the perspective of extant message reception theory such as the elaboration likelihood model or the heuristic-systematic model. For example, several conditions must exist before the contagion model can explain the dissemination of information. Information salient to the individual will be treated differently than information which is not (O’Keefe, 2006). Human’s have limited cognitive resources and continually select which stimuli to attend to and what information to retain in our memory. Information that is not salient to the individual is unlikely to receive the same scrutiny as information which is. Additionally, individuals must be capable of comprehending the messages content. Information that is incomprehensible to the individual is unlikely to be regarded as salient and may be either accepted without question or rejected outright. Information that is considered salient will be evaluated within the framework of an individuals existing knowledge. Underdeveloped messages may be unable to satisfy an individual’s threshold for certainty regarding the veracity of the message and result in it being rejected. This initial rejection may lead to the development of the inoculation effect in individuals. Individuals incapable or unmotivated to engage in cognitive processing may be forced to rely on simple heuristics such as source credibility and message length when evaluating a message’s veracity (O’Keefe, 2002).
The cognitive processing of messages has implications for the structuring of networks. Individuals are likely to have stronger ties with peers and knowledge repositories which they perceive as credible than those they perceive as unreliable. In contrast, rejection of information as irrelevant or unreliable may serve to weaken ties between a network’s nodes. These patterns of behavior operate similarly when dealing with human sources, non-human agents and knowledge repositories. For example, a book with information that has been proven to be out of date is unlikely to be consulted. Likewise, a person who has proven to be ill informed in the past is not likely to be consulted regarding a future decision concerning the same matter. Individuals who maintain contact with these information sources may be hesitant to integrate information originating from them into their body of knowledge and subsequently transmit it to others in the network.
In addition to the simple principle of homophily, individual differences will likely prove to be an important factor in the structuring of networks. Future research ought to focus on how individuals cognitively evaluate the suggestions and contributions of anonymous individuals online and its resulting effect on network structure. Furthermore, research should be conducted which examines how individuals evaluate information from non-human agents as well as knowledge repositories. Individual differences are important to network structure; it’s not just who you know, it’s who you are.
Works Cited
Contractor, N. S., & Monge, P. R. (2002). Managing knowledge networks. Management Communication Quarterly, 16, 249-258.
Contractor, N. S., Lecture
O’Keefe, D. (2002). Persuasion: theory and research. Thousand Oaks, CA: Sage.
Monge, P. R., & Contractor, N. (2003). Multitheoretical, Multilevel Models of Communication and Other Organizational Networks . In Theories of Communication Networks (pp. 293-327). New York: Oxford University Press.
Postmes, T., & Baym, N. (2005). Intergroup dimensions of the Internet. In J. Harwood & H. Giles (Eds.), Intergroup communication: Multiple perspectives (pp. 213-238). New York: Peter Lang.
It’s Not Just Who You Know, It’s Who You Are: Individual Difference on Network Structuring
Several theories have been proposed to explain the spread of information and behaviors via social networks. Contagion theory seeks to explain the dissemination of information, messages, attitudes and beliefs by applying a biological metaphor to social networks (Contractor and Monge, 2002). Its primary tenant is that mere exposure to different ideas, attitudes and behaviors can bring about a change in the previously existing ideas, attitudes and behaviors (Monge & Contractor, 2003). While this may be a necessary condition to provoke change, it certainly is not a sufficient condition. Rather, the spread of ideas is likely contingent upon attributes of individual network nodes, the structure of the existing network, as well as cognitive evaluations of messages by their recipients.
The theory of homophily holds that individuals tend to develop networks of others like themselves which are based on social categories developed from key social dimensions such as age, gender, race, professional afflictions and other demographic characteristics. In short, “birds of a feather flock together”. Which demographic characteristics are salient for the formation of a social identity is a result current situational demands and the networks structure (Monge and Contractor, 2003). One of the major implications of contagion theory is that people who are in regular contact will have similar attitudes, beliefs, and ideas. This line of reasoning suggests that contagion theory contributes to the creation of a group culture among relatively homogenous individuals who are in frequent contact. However, even among relatively homogenous groups differences between individual nodes may inhibit the transmission of ideas and beliefs.
The principle of homophily suggest that external similarities between network nodes lead to the creation of networks between similar individuals. However, when networks are created online in the absence of individuating information, external traits of nodes may be reduced in their importance (Postmes & Baym, 2005). Rather, individuals who identify with one another online may fall back on social identities created from similar attitudes or interests. As a result, online homophily has the potential to enhance the contagious spread of ideas and beliefs. Social identities have the potential to influence an individual’s thoughts and actions as a result of self-categorization and social identification. These processes may lead to group norms and values being internalized. Therefore, information that is salient to the social identity of an online group may be more likely to be disseminated within the group via a contagion model and subsequently retained and internalized among group members than the same information among individuated offline groups.
Contagion theory suggests a centralized distribution pattern of information around key nodes with the infected nodes radiating outwards. Proximal nodes are more likely to be exposed than nodes that are further away. Proximity increases the potential that individuals have contact and learn from one another (Monge & Contractor, 2003). The potential to develop communicative links among nodes decreases drastically with the increase of distance. Likewise the theory of electronic proximity suggests that far-flung ties resulting from new media would free information from it’s geographically based dispersal pattern. However, research has indicated that some technologies, such AOL instant messenger, are used as often to talk to individuals who are geographically proximal as to individuals geographically distant. Furthermore, the primary use of email has been found to be scheduling face-to-face meetings (Contractor, Lecture). Therefore, it is reasonable to assume that while new media may provide a mechanism for the distribution of ideas and beliefs, information dispersal will still consist of a tight geographically collocated cluster with much looser halo of “infected” nodes as geographical distance increases. This pattern is representative of a small world network and can provide insight into the spread of ideas and attitudes through a network. Small world networks can be defined as those “where nodes have a high degree of local clustering with a small fraction of nodes (that is, these nodes are interconnected to one another), while at the same time being no more than a few degrees of separation from all of the remaining nodes” (Monge & Contractor, 2003). Small world networks have a few connections to other distant nodes which serve as short cuts for information spreading across a network.
The contagion theory assumes that mere exposure is sufficient to spread information and beliefs. However, message reception by human nodes should be considered from the perspective of extant message reception theory such as the elaboration likelihood model or the heuristic-systematic model. For example, several conditions must exist before the contagion model can explain the dissemination of information. Information salient to the individual will be treated differently than information which is not (O’Keefe, 2006). Human’s have limited cognitive resources and continually select which stimuli to attend to and what information to retain in our memory. Information that is not salient to the individual is unlikely to receive the same scrutiny as information which is. Additionally, individuals must be capable of comprehending the messages content. Information that is incomprehensible to the individual is unlikely to be regarded as salient and may be either accepted without question or rejected outright. Information that is considered salient will be evaluated within the framework of an individuals existing knowledge. Underdeveloped messages may be unable to satisfy an individual’s threshold for certainty regarding the veracity of the message and result in it being rejected. This initial rejection may lead to the development of the inoculation effect in individuals. Individuals incapable or unmotivated to engage in cognitive processing may be forced to rely on simple heuristics such as source credibility and message length when evaluating a message’s veracity (O’Keefe, 2002).
The cognitive processing of messages has implications for the structuring of networks. Individuals are likely to have stronger ties with peers and knowledge repositories which they perceive as credible than those they perceive as unreliable. In contrast, rejection of information as irrelevant or unreliable may serve to weaken ties between a network’s nodes. These patterns of behavior operate similarly when dealing with human sources, non-human agents and knowledge repositories. For example, a book with information that has been proven to be out of date is unlikely to be consulted. Likewise, a person who has proven to be ill informed in the past is not likely to be consulted regarding a future decision concerning the same matter. Individuals who maintain contact with these information sources may be hesitant to integrate information originating from them into their body of knowledge and subsequently transmit it to others in the network.
In addition to the simple principle of homophily, individual differences will likely prove to be an important factor in the structuring of networks. Future research ought to focus on how individuals cognitively evaluate the suggestions and contributions of anonymous individuals online and its resulting effect on network structure. Furthermore, research should be conducted which examines how individuals evaluate information from non-human agents as well as knowledge repositories. Individual differences are important to network structure; it’s not just who you know, it’s who you are.
Works Cited
Contractor, N. S., & Monge, P. R. (2002). Managing knowledge networks. Management Communication Quarterly, 16, 249-258.
Contractor, N. S., Lecture
O’Keefe, D. (2002). Persuasion: theory and research. Thousand Oaks, CA: Sage.
Monge, P. R., & Contractor, N. (2003). Multitheoretical, Multilevel Models of Communication and Other Organizational Networks . In Theories of Communication Networks (pp. 293-327). New York: Oxford University Press.
Postmes, T., & Baym, N. (2005). Intergroup dimensions of the Internet. In J. Harwood & H. Giles (Eds.), Intergroup communication: Multiple perspectives (pp. 213-238). New York: Peter Lang.
