Bodong Chen

Crisscross Landscapes

Notes: Contractor, N. (2009). The Emergence of Multidimensional Networks



Citekey: @Contractor2009-sv

Contractor, N. (2009). The Emergence of Multidimensional Networks. Journal of Computer-Mediated Communication: JCMC, 14(3), 743–747.


Summarize: This short essay makes some really great points about the emergence of multidimentinoal networks (multimode, multiplex) in the context of Internet evolution.


Yet there are some success stories that suggest the need to understand the social factors that shape the use of technologies to create and sustain organizational, interorganizational, and community knowledge networks. (p. 1)

as developments in information and communication technologies continue to reduce or eliminate the potential logistic barriers to our communication and knowledge networks, it becomes increasingly important to identify the various social factors that enable or constrain the development of these network linkages. (p. 1)

This essay outlines four recent developments that serve as an intellectual springboard to significantly advance our ability to understand and enable these multidimensional networks. (p. 1)

Advances in theorizing the social motivations for emergence of multidimen- sional networks (p. 1)

he need to theorize about the emergence of linkages in ‘‘multidimensional networks’’—where the nodes are people as well as ‘‘nonhuman agents’’ such as documents, datasets, analytic tools, and concepts (or keywords) (Hollingshead & Contractor, 2002). The links among these nodes would include, for instance, people accessing/creating/citing documents, documents that report results based on a dataset, analytic tools used to investigate a dataset, keywords associated with certain documents,andsoon. (p. 2)

In intellectual terms, we ask the question: What are the social motivations that help us understand why we as individuals seek to forge, sustain, or dissolve our knowledge network ties with other human and nonhuman agents? (p. 2)

including social network theory (Monge & Contractor, 2003), network society (Castells, 2001) and actor-network theory (Latour, 2005). (p. 2)

Development of cyberinfrastructure/Web 2.0 to capture vast amounts of relational metadata (p. 2)

The Web 2.0, Semantic web, and cyberinfrastructure technologies that have enabled the multidimensional networks described above also provide the opportunity to capture, tag, and manifest high-resolution high-fidelity relational ‘‘metadata’’ (i.e., which node is connected to which other node) from these multidimensional networks. These include (i) technologies that ‘‘capture’’ communities’ relational metadata (Pingback and trackback in interblog networks, blogrolls, digital traces, data provenance), (ii) technologies to ‘‘tag’’ communities’ relationalmetadata(rangingfromDublinCoretaxonomiestofolksonomies(‘wisdom of crowds’) like tagging pictures (Flickr), social bookmarking (, digg. reddit, LookupThis,BlinkList),socialcitations(,sociallibraries(,, social shopping (SwagRoll, Kaboodle,, and social networks (FOAF, XFN, MySpace, Facebook), and (iii) technologies to ‘‘manifest’’ communities’ relational metadata (Tagclouds, Recommender systems, Rating/Reputation systems, (p. 2)

the Internet is the world’s largest social science observatory. (p. 3)

Opportunity for design-assisted theory construction (p. 3)

Recent scholarship (Bar & Sandvig, 2008; Lessig, 2006) has documented how software code embedded in technologies has substantial influence on the structuring of society and social interactions. (p. 3)

related to learning analytics system integrity. (p. 3)

e have the ability to design new technological features not as an end in itself but a means towards an end–theory construction. Not unlike the design of laboratory experiments, we have the opportunity to embed in the ‘‘design code’’ of technologies various theoretical mechanisms and systematically observe the manner in which these mechanisms interplay with social behaviors. (p. 3)

Advances in confirmatory network analysis to empirically test structural signatures in multidimensional networks (p. 3)

Recent advances in the development of statistical techniques such as Exponential Random Graph Modeling (also known as p*) in social network analysis have created the opportunity for a new generation of ‘‘confirmatory network analysis’’ - to empirically test cross-sectional and longitudinal hypotheses about the extent to which multiple theoretical motivations, operating at multiple levels of analysis, contribute to the emergence an observed multidimensional network (Robins et al., 2007). (p. 3)