Many thanks to John Breslin for organising Irelands first Webcamp, last Wednesday 7th March. The afternoon was an enlightening look into the development, search, analysis and productive uses of social networks.
I’ve wiki’d some notes on event (Ed – 2013, notes below).
Particularly interesting was the response of designated Bebo’s spokesperson, Mark Tarbatt of webvertising firm Generator, to my questions about potential Bebo censorship. The impression Mark (whose firm seem solely responsible for selling branding on Bebo, at least in Ireland) gave was that, in the event of a conflict between a user video or community (the example I provided was a hypothetical ‘killer coke’ video on Votetube’s bebo profile) and a Bebo advertiser, such a user or community could be removed. This seems credible given that Mark stated Bebo’s recent adoption of comment moderation occurred not in response to problems of user abuse or sexually explicit spam, but to satisfy the desire of Coca Cola (a bebo advertiser) to prevent ‘harassment’ on it’s branded bebo site.
A quick search of Bebo indicates the existence of just such a conflict.
Notes
Topics, tags and trends in the blogosphere
Looked at (inter)relationship between blogs, and their topics
sought topic related interlink structure
7k blog data set
Muhammad cartoon controversy tracked
Blogosphere user centric vs topic centric Usenet
Clutters of topic sharing blogs are short lived
Strong clusters hold users
but users drift from topics over time
Extreme topic drift increases user falloff
Tags poor method of tracking blog post content
Concept clustering better
A list blogs more similar to one another
more topic focused, consistent – authorities
tags chosen for comprehensibility
tight networks of clusters
C list blogs have higher user entropy
little or no inward linking
Notes
How were A list bloggers defined?
What about Maven Bloggers / influential but narrow popularity – Malcolm Gladwell’s Idea articulated in ‘The Tipping Point‘
Does user topic drift account for primacy of link aggregator blogs / communities
Collecting community wisdom: integrating social search and social navigation
2 Aspects – social browsing and social search, combined to augment search of Association for Computing Machinery Digital Library (popular computer science pub database – with browsing and search navigation)
KnowledgeSea – social browsing
Collates anonymized browsing history
Provides the capacity for digg like ratings and annotation
iSpy – social search
Reranks results based on previous keyword searches by user group
Icon based visual cues on rating etc
Combined and integrated both systems – increased search efficacy
Notes
where’s the hook for students to build this system – are legal restrictions keeping the content closed ?
would it not be better to use off the shelf digg / del.icio.us like solutions ? alternately light weight sem web client on top of existing networks of databases ?
Quirky mystery meat interface – why do academic database sits have to be so unusable
Annotations could be used to increase utility of abstract
No information provided on stat significance of results
Control group browsing history is artificially useful seed for social group
How to compare trained systems fairly?
The demand for search in a social network
Founders of Bigulu – Bebo search, 2 Phd students
May expand to other networks
Crawls Bebo to allow superior profile search based on keyword, age, gender, location
Estimate Bebo at 7m users not 25m as claimed !
Slow linear growth of Bigalu
Sem web API would aid search and data migration
New features – inc user popularity (like Facebook radar)
Inbound links as social distance cue to search
limitations on social scraping due to private profiles etc
Notes
What is user persistence like?
Could they be underestimating Bebo network due to islands (isolated nodes or clusters – social darknets) ?
Is ‘low attention span’ really a function of high efficacy expectation
Are assumptions about viral growth of Bebo correct? Implied signup active network discrepancy
Where is the knowledge: reflections on social networking in corporate environments
(Virtual) ethnographic study of collaborative work practices
IBM Dublin software lab
Technology as tool inseparable from culture
technofetishism (sysadmin) vs fluffy-bunnies (people persons)
tools should be tailored to users
human guides to knowledge repositories vital
social networks facilitate knowledge aquisition
Lotus Messenger tool
IM – integrates: blog, wiki, org chart, social bookmarks, presence, contact details
Used to request ad-hoc meeting attendance
Used to reduce steps to data acquisition
Documents can link to individuals
Real time back channel in meetings
Data Retention
Legal and practical requirements to archive data
creates and enforces etiquette
no interdiction on personal contact – social honor enforces
Successful campaigns on the Bebo social network
Small list of clients – A list Irish sites
Daft, Eircom, RTE, Bebo etc
Sell to ad agencies and brands
Internet only 1% Irish advertising market
UK internet ad budget = 2X Irish ALL media budget
Ireland € 24 per user, UK € 80 per user
Main income to Bebo (other than VC) = ads
All major Irish net spending brands advertise
Brand budget (overall) – 140k – 600k (top ten)
Some brands shy away from user content areas – use frontpage etc
Bebo top site for under 17 in Ireland (comscore)
Average visit 75mins ! (of 3 hour session)
95% reach
drops off list of top sites in older categories
Use by corps like Mcdonalds under pressure not to kidvertise on TV
Relevance, customer interaction / relationship to brand
Options
Sidebar ads
Branded profiles (eg: Disney Cars)
Branded Bebo mail window
Clickable in video advertisement tickers
Texter widget – Moco – € 2 a week
Anti sponsor brand comments / groups (eg: killer coke) would probably be removed
Notes
Ethics of Bebo spread? Via address book spam?
Growth of Facebook a threat?
Lack of direct access in school has not limited popularity
Corruption of utility of social media in ‘brand interaction’
Interesting to note bebo added comment moderation not in response to cyber bullying but concerns of Coke – insistence on stifling branded profile criticism
Texter widget is misleading
initially video states that service is free
only mentions charges towards end of video
Keynote: Social network analysis: 1987-2007
Any kind of network can be mathematically mapped
from social networks to computer networks
social / organisational network analysis
Inflow software
‘Highly between person’ connects networks
analogous to Gladwells superconnector
David Krackhardt – organisational structure related to power
Hierarchy, network position, and network knowledge – knowing the map
Six Degrees of Separation = Golden myth
original study flawed (response bias)
Noah Friedkin – UC Santa Barba – Social networks have a horizon
2 step clarity – blind after 4 connections max
outer reaches of network are invisible
Mark Granovetter – one or at most 2 intermediaries useful
in context of information (job) seeking
direct ties most useful of all
IBM and Valdis Krebs – adaptive organisations have higher average reach
data acquired through survey and interview, document sharing etc
Pharmaceutical firms market to opinion leaders
use social network analysis to target doctors who influence drug prescription of contemporaries
Formalising of common interest networks
Bounded vs unbounded (not task / job delimited) networks
Network weaving = analyzing networks to build communities
9/11 hijacker network – built on media published data
conclusion – project teams are similar
task focused group structures do not vary based on task
False positives can emerge from social network analysis
limited inferences can be reasonably drawn
Infrastructures are built on effectiveness not resilience
useful for network attacks
Notes
Evolution of social networks over time? – differ based on organisation evolution? – loose voluntary network migration
Richness of less visible ties?
Does similarity of group structure apply cross culturally?
Group Discussion – Future of social networks
Existing Networks
tribe, livejournal -> myspace -> bebo -> facebook
Do super connectors lead network migration / adoption?
Do teens socialise on social networks, or just mirror existing real world acquaintance?
do users actively resist socialising
are there different socialisation patterns culturally, network determined
Book – republic.com – reinforcement of preexisting connections
social networks not scale free
Social networks as dating substitute – exhibitionism
display, personality branding
rating and identity definition
utility of maintenance of connections over time
forking elitist / domain specific networks
Social networks -> open id -> light sem web clients -> device based ad hoc attentional aggrigators
carrying groups between networks
open attentional data
open identity data
balance of privacy, security, reputation and freedom
Hardware versions of my blog log / twitter
mobile ubiquitous anonymised positional aggregation
variety of possible consequences
loss of privacy vs great utility
branded flash mobs – ala Dublin’s black parade
social network manipulation and politicisation
SNA used to infer guilt by association / track dissidents
pattern matching by employers
Comparative safety of blogging – distance from ‘online friends’
Exaggerated fears of predation
Reputation as currency
Gareth Stack 
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