Assignment submission for SHU MA in Technical Communication - Year 2 Social Media course

1. Module: 55-7626-00N-A-20123 – Social Media Use in Organisations (A-2012/3)
Social Network Analysis
of M2M Organisations
Lee James Cox
B0049872
MA in Technical Communication
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2. First some definitions
Social Network Analysis (SNA) is the study of structure1. It is the mapping and
measuring of relationships and flows (ties) between members (nodes) within a
network.
Machine to Machine (M2M) refers to the technology that connects:
a. a device (such as a sensor or meter) to capture an event (such as temperature,
inventory level, etc.)
b. which is relayed through a network (wireless, wired)
c. to an application (software program), that translates the captured event into
meaningful information (for example, items need to be restocked).
M2M Organisations include device, network and application providers; as well as:
• Enterprise Customers: provide the services to end-users, e.g. Coca Cola, British Gas
• Platform Providers: equipment and solution providers to operators and others
• System Integrators: build solutions to join up incompatible systems
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Node Node
Tie

3. Five things to first consider about SNA
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1. The first endeavour should always be to define what the Nodes and Ties mean.[2] For
our M2M analysis, the nodes are organisations and ties are contractual relationships.
2. Nodes can have different weightings of importance, e.g.
– Size (revenue/subscribers)
– Geography
– Track record
– Associations
– Other segmentation attributes
3. Ties have characteristics that matter when it comes to identifying things like leadership,
influence and strength e.g.
– Direction (one-way, both)
– Quantity
– Contract date
– Value
– Frequency
4. Matrix, graphs and other visualization tools are important for analysis and measurement.
– Tools like NodeXL will be required for any network of reasonable size
– Considerable time is usually required to capture and keep the data up to date.
– The M2M example in later slides shows just a few of the tens of thousands of Enterprises, 200+ Operators &
300+ Application Providers that Jasper, Vodafone & Ericsson have as M2M partners!
5. The perspective of the analysis can centre on the complete network (socio) or an
individuals personal network (ego).

4. Social-centric or Ego-centric SNA?
Social-centric (complete network)
a. Allows analysis of nodes and ties in comparison to wider
network, e.g.
– Are Operator relationships tightly bonded, diversified or
constricted?
– Is there density/clustering of contracts within a geography
such as Europe, or are there more cross-continent?
b. Identifies behaviours affected by positions and
connections, e.g.
– Does the number of application provider ties influence the
number of ties a platform provider has?
– Does the distance between application and platform nodes
affect the number of operator relationships?
Ego-centric (personal network)
a. Only ties directly with the focal organisation (Jasper)
plus those Jasper is aware of are included.
b. Perception is reality and opinions count. Subjective
attributes are likely to have weight in many business
matters
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Figure 1 –Socio-centric view of the sample M2M Eco-System
Figure 2 – Ego-centric view of Jasper M2M Network

5. Visualization[3] can also reveal positional relationships
• Operators have the highest degree
centrality. AT&T is most central of the
operators and is the longest established
with largest customer base.
• Application Providers have the highest
closeness centrality. They work with
multiple operators but rarely direct with
Enterprise customers.
• Device/SIM and Platform Providers are
structurally equivalent nodes.
• System Integrators are the most peripheral,
having the smallest number of connections.
• Enterprise Customers has the highest
betweeness centrality providing the only
path to System Integrations
• No groups of nodes are connected to each
other (cliques). However if the definition of
ties were extended beyond ‘contractual’
then informal or personal relationships
would show all nodes in this extracted view
as being connected.
Operators
Enterprise Customers
Device/SIM
Application Providers
Platform
System Integrators
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6. Benefits & Limitations of SNA
Benefits Limitations
Provides framework to describe any complex
network.
Collecting and maintaining source data can be
difficult
Identifies important individuals and the influence
they have
Does not describe meanings, motives or explain
why actions happen, e.g. why a contract was won.
A typological analysis is more suitable.
Can identify previously unrecognised sub-groups
through visual clusters
Little examination of important attributes such as
attitudes, opinions and behaviours that may be
helping or hindering relationships
Highlights areas for further inquiry and possible
improvement, e.g. gaps
More sensitive to data omissions than other
surveys. >75% sampling is required.[4]
Even weak ties may be revealed as important for
bridging disparate groups
Privacy can be ignored when views of others
contribute to the analysis.
Useful for track changes over time to reveal paths. Visualization can lead to over simplification and
misreading of results. E.g. Network measures such
as density can be easily misrepresented when
networks of different sizes are compared.
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7. Other take away learning’s from SNA
1. Social Network Analysis is not necessarily restricted to connections from
tools such as Facebook or LinkedIn. SNA can be applied to a wide range
of network subjects, such as how diseases spread, mapping films and
interaction of characters, influence of language throughout the world,
etc.
2. SNA focusses on relationships rather than attributes of the ‘nodes’ for
their own sake, or the ideation behind the relationship.
3. A Social Network does not in itself encourage co-operation or collective
action. Community tools such as Online Forums lend themselves better
to co-ordination of action.
4. Connections within business networks often reveal companies tied to
competitors. This has implications for trust and potential leaks within a
social network.
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8. References
[1] Wellman B, Berkowitz SD (1977). Social structures: a network approach. Greenwich: JAI Press.
[2] Pinheiro, C. (2011). Social Network Analysis in Telecommunications. John Wiley & Sons.
[3] Based on Davies R (2011). Network Visualisation and Analysis, Cambridge.
[4] Borgatti, Carley & Krackhardt (2006).
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