COMMUNICATION: SMALL GROUPS & INTERNET

1. COMMUNICATION: SMALL GROUPS & INTERNET Studies of network effects on communication began at MIT in 1940s with Alex Bavelas & Harold Leavitt’s experiments on collective puzzle-solving using cubicle-constrained channels for passing information. For simple tasks, wheel and Y have faster puzzle-solution times. For complex tasks, circle and all-channel form are quicker. Centralization is moderating factor: Clear info flows more rapidly in centralized nets, but unevenly distributed & ambiguous info faster in decentralized. Wheel/star Circle Chain Y Information decays with network distance: Where d is path distance (length), probability of i passing info to j given k independent paths is: Small group research revived in 1990s as orgs searched for optimal internal structures & external network embeddedness (Katz et al. 2004).

2. An MTML Framework Peter Monge & Noshir Contractor (2003) proposed an integrative multitheoretical multilevel (MTML) framework of core mechanisms to explain the evolution of complex adaptive communication networks. Table 1.1 classifies as the core theories as Self-Interest, Mutual Self-Interest & Collective Action, Cognitive, Contagion, Exchange & Dependency, Homophily & Proximity, and Network Evolution MTML “seeks to examine the extent to which the structural tendencies of organizational networks are influenced by multitheoretical hypotheses operating at multiple levels of analysis” (p. 69). Homophily implies preferred ties to other actors sharing same attributes H6: The network demonstrates a structural tendency toward choice, mutuality, transitivity, and … a differential tendency toward choice of other actors in the same block. Exogenous attributes of actors Structure of the focal network Exogenous relations in networks Endogenous mechanisms

3. THE INTERNET – Invented by Al Gore? • Communication technology of Internet followed S-shape diffusion curve: • 1968 DARPA creates ARPAnet for defense contractors • 1970 Five nodes: Stanford, ULCA, UCSB, Utah, BBN • 1974 Transfer Control Protocol (TCP) specification • 1984 Internet with 1,000 host computers converts to TCP/IP Internet is a packet-switching network. Packet is a data unit created by TCP software for transmission using domain names and Internet Protocol addresses. File to be transmitted is split into many small packets, each assigned a number, containing information about its content and destination Packet data streams travel via network-of-networks (server computers or “hosts”), following different paths, and may be repackaged enroute At destination, original file reassembled from packets for reading/viewing

4. Exponential Growth of Hosts SOURCE, William F. Slater, III By 2010, will 80% of the Planet Earth be on Internet!?

5. The WORLDWIDE WEB Web browsers emerged by the 1990s for finding and downloading Webpages, data, documents, multimedia. In 1989, Tim Berners-Lee invented the World Wide Web at CERN’s European Particle Physics Lab, applying HyperText Markup Language (HTML). He now directs the W3 Consortium of orgs that develop interoperable technology standards. Commercial firms that market directories & search engines cover only small % of all Web content. But, data from their site- and page-links enable researchers to visualize the Internet and Web social structures as network diagrams.

6. A Geographic Internet Map John Quarterman mapped geographic locations of Internet hosts as symbols on a world map (The Matrix: Computer Networks and Conferencing Systems Worldwide. 1990. Digital Press). Count N of hosts in major cities and countries, then plot on world map as colored circles proportional to size. Note super-clusters in North America (purple circle ≥ 1 million hosts) and Europe (predominantly blue circles). What evidence do you perceive of North-South “digital divide” paralleling their economies? SOURCE: Internet Domain Survey July 1999 <http://mappa.mundi.net/maps/maps_007/>

7. The Internet Mapping Project Internet Mapping Project started at Bell Labs in 1998, spun-off to Lumeta Corp in 2000. Map shows frequent trace-route-style path probes, one to each registered Internet entity. Objectives: acquire, save topological data over long period, to analyze routing problems, service-denial attacks, and graph theory. “The early results looked like a peacock smashed into a windshield.” “We have no interest in the specific endpoints or network services on those endpoints, just the topology of the ‘center’ of the Internet. The database should help show how the Internet grows. We think we can even make a movie of this growth someday.” Internet map published in Wired (1998), for 100,000 nodes based on “half a dozen simple rules, simulating various springs and repelling forces.” SOURCE: <http://research.lumeta.com/ches/map>

8. Mapping Major ISPs This Internet map has a diameter of ~10,000 ‘pookies’ (an arbitrary distance unit)

9. How to Become Very Popular on Google By 2002, about 95% of browsing used Microsoft’s Internet Explorer, but 75% of external referrals on most Websites were from Google. Google’s hypertext search software, PageRank™, for ranking Webpages using link structures to indicate individual page values. Google treats page A’s citation of page B as a “vote” by page A for page B. But, Google also takes into account A’s page rank. Votes cast by “important” pages count more heavily, helping make other pages more “important.” More generally, weighted-status methods calculate an ego’s power within a network as a function of all its alters’ powers. • “We assume page A has pages T1...Tn which point to it (i.e., are citations). … C(A) is defined as the number of links going out of page A. The PageRank of a page A is given as: • PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn)) • Note that the PageRanks form a probability distribution over web pages, so the sum of all web pages' PageRanks will be one. PageRank or PR(A) can be calculated using a simple iterative algorithm, and corresponds to the principal eigenvector of the normalized link matrix of the web.” • Ian Rogers.“The Google PageRank Algorithm and How It Works.”<http://www.iprcom.com/papers/pagerank/>

10. INTERNET in EVERYDAY LIFE “Cyberspace” is the social counterpart to the Internet’s physical technologies. Social network researchers examine how Internet users adapt their ties to its constraints and vice versa. Barry Wellman asked a variant of The Community Question: “How do large-scale divisions of labor affect – and are affected by – smaller-scale community of kith and kin?” How have Internet & community transformed one another? How is the Internet being incorporated into everyday life? Does the Internet multiply, decrease, add to - other forms of communication? - overall communication? How is the structure of interpersonal relations affected? How does everyday life affect the Internet?

11. THREE INTERACTION MODES Are communities shifting from densely-knit “little boxes” to “glocalized” nets (sparsely-knit with clusters, linking households locally & globally) to “networked individualism” (sparsely-knit, linking individuals with little regard to space)?

12. Rise of Networked Individualism Society moving from relations bound up in groups to a multiple network – and networking – society, characterized by: Longer-distance ties, sparsely-knit, loosely-bounded, multi-foci Transitory, weaker ties, less caring for strangers = alienation? Flexible networks are major sources of social capital • CHANGES DRIVING NETWORKED INDIVIDUALISM • Transportation & communication becoming more individualized • Affordable, portable computerization allows greater personalization • Multiple employers, sequentially and contemporaneous • Separation of work and home as physical places • Working away from workplace: Telework, flextime, road warrior • Dual careers – multiple schedules to juggle Barry Wellman. “Netting Together” <www.ksg.harvard.edu/digitalcenter/ event/wellman%20workshop.ppt>

13. NETVILLE WIRED Case study of “Netville,” a new planned suburb of Toronto, offered clues about how the Internet becomes embedded into everyday lives. Some residents chose Bell Canada’s no-cost Internet services. Keith Hampton field ethnography was complemented by a survey about Netville residents’ Internet usage and networking. One year after moving in, wired Netville residents had enhanced local ties & expanded weak ties. Compared to nonwired, wired people: (1) had more social contact, especially > 500 km; (2) gave more help: childcare, home repair; (3) received help from friends and relatives, esp. 50-500 km. Altho getting wired expectedly sustained more distant community ties, it surprisingly also increased local face-to-face neighboring: “The local becomes just another interest.” Keith Hampton & Barry Wellman. 2003. “Neighboring in Netville.” City & Community

15. Conclusion: Community Transformed • Connectivity changes by all available means - door-to-door, place-to-place, and person-to-person • Less-solidary households, and more networked & virtual work relationships • New forms of community, partial memberships in multiple communities Partial communities comprised of shared, specialized interests Networked society is both more uncertain & more maneuverable – for people with the tools & skills