Tag Archives: social networks

Facebook network

A sociogram of my Facebook networkI am currently trying to catch up on the Coursera MOOC on social network analysis . My main aim in taking the course is to force myself to learn about using Gephi for network analysis. The course so far has been clear and well presented but its early stages. Also, using Gephi on the Mavericks version of OSX has been a pain largely due to Java as Gephi won’t run on the default install of Java. The solution can be found on the Gelphi forums here although I’m still having some problems with Java.

I don’t use Facebook much and was a bit surprised at the density of the network as a whole but having that number of sub-clusters was less surprising considering the stop-start nature of how the network developed. I’ll have to find out who the single unconnected nodes are once the Java issues have been resolved.

LinkedIn network map

This is a very short post on my LinkedIn network mapLinkedIn network map

The identification of three distinct clusters of contacts is interesting and (kind of) makes sense. What is particularly useful is identifying the links between clusters that ‘should’ be stronger. In terms of developing a professional personal learning network as part of a personal learning environment, LinkIn maps  look  useful as a visual “sense-making” tool and for identifying your network’s strengths and weaknesses. Next is to attempt to work out why some components of my networks look weak, if these weaker areas can and should be strengthened and, if so, how?

Social Network Analysis and Digital Data Analysis

Notes on a presentation by Pablo Paredes. The abstract for the seminar is:

This presentation will be about how to make social network analysis from social media services such as Facebook and Twitter. Although traditional SNA packages are able to analyse data from any source, the volume of data from these new services can make convenient the use of additional technologies. The case in the presentation will be about a study of the degrees of distance on Twitter, considering different steps as making use of streaming API, filtering and computing results.

The presentation is drawn from the paper: Fabrega, J. Paredes, P. (2013) Social Contagion and Cascade behaviours on Twitter. Information 4/2: 171-181.

These are my brief and partial notes on the seminar taken live (so “typos ahead!”).

Looking at gathering data from social network sites and on a research project on contagion in digital data.

Data access requires knowledge of the APIs for each platform but Apigee details the APIs of most social networks (although as an intermediary, this may lead to further issues in interfacing different software tools, e.g., Python tool kits may assist in accessing APIs directly rather than through Apigee). In their research, Twitter data was extracted using Python tools such as Tweepy (calls to Twitter) and NetworkX (a Python library for SNA) along with additional libraries including Apigee. These tools allow the investigation of different forms of SNA beyond ego-centric analysis.

Pablo presented a network diagram from Twitter using NodeXL as ego-networks but direct access to Twitter API would give more options in alternative network analysis . Diffusion of information on Twitter was not possible on NodeXL.

Used three degrees of influence theory from Christakes & Fowler 2008. Social influence diffuses to three degrees but not beyond due to noisy communication and technology/ time issues leading to information decay. For example, most RTs take place within 48 hrs so tends not to extend beyond a friends, friends friend! This relates to network instability and loss of interest from users beyond three degrees alongside increasing information competition as too intense beyond three degrees to diffusion decomposes.

The  direct research found a 3-5% RT rate in diffusion of a single Tweet. RT rates were higher with the use of a hashtag and correlate to the number of followers of the originator but negatively correlates to @_mentions in the original Tweet. This is possibly as a result of @_mentions being seen as a private conversations. Overall, less than 1% of RTs went beyond three degrees.

Conclusion is that diffusion in digital networks is similar to that found in physical networks which implies that there are human barriers to communication in online spaces. But the research is limited due to the limits on access to Twitter API as well as privacy policies on Twitter API. Replicability becomes very difficult as a result and this issue is compounded as API versions change and so software libraries and tools no longer work or no longer work in the same way. Worth noting that there is no way of knowing how Twitter samples the 1% of Tweets provided through the API. Therefore, there is a need to access 100% of the Twitter data to provide a clear baseline for understanding Twitter samples and justify the network boundaries.

Points to importance that were writing code using R/ Python preferable as easier to learn and with larger support communities.

WeekNotes [07032014]

A bit of a delay in posting this but last week I:

Attended seminars on ethnographic network analysis and on visual presentation in business decision-making. Both were interesting presentations of research projects at different stages: the former at a fairly early stage and the latter with the fieldwork completed and a good deal of the analysis completed.

I was interviewed for a small-scale research project.

Edited the methodology section of a draft paper on managers’ perceptions of their roles in facilitating workplace learning.

Further developed my largely quantitative analysis of two Twitter communities.

 

Freelance Film workers in Beirut: An Ethnographic Network Analysis by Arek Dakessian,

These are some rough notes on this presentation from a series of seminars run by the Social Network Analysis Group in Scotland (SNAS). The intro to the talk states:

Arek is a first year PhD student in Sociology at the University of Edinburgh, and his research mainly revolves around networks of cultural production in cities, specifically Beirut. He aims to unpack the relationship between processes of cultural production and consumption and the day-to-day political economy of his city.

His presentation titled “Freelance Film workers in Beirut: An Ethnographic Network Analysis” is the same title he gave a paper currently under review, but his presentation would focus more on doing a dual mode social network analysis based on ethnographic data and some of his dissertation findings.

This is a small informal seminar group. My notes will be very partial and live (and with poor spelling and grammer).

Announced that SNAS as received some funding to become more research-focused and link with the other universities in Scotland and to run two workshops in 2014. The workshops will be focused on what people are doing in Scotland on SNA and whether there is potential for collaborative research.

Arek’s research is on networks of cultural producers and  mainly film-makers in Beirut. He will be talking about the experience of practicing and the research experience of conducting SNA, especially shifting from ethnography and mixed method network analysis.

Narratives of Bierut dominated by bombs and nightlifes. The reality is more complex (as you’d expect). Consists of approx 18 different sects cutting across cultural and ethic boundaries; also 80k + non-national domestic staff (who are not allowed to practice their religions as not generally one of the 18 official sects; also Palestinian refugees based in camps as well as refugees from Syria. So have clear interplay between politics and culture and complex networks of cultural production.

Arek’s ethnographic research on social capital in networks of cultural production – essentially how to gain access to those networks and to “make it”.Initially completed some basic SNA involving centrality but not fully developed.

Ethnographic SNA is difficult in terms of sampling and bounding the network as well as data gathering. Using textual data such as credit lists linking people, objects and events. To ethnographically understand “what is going on” – identifies who is not included in the textual data.

Seeks to enhance SNA through using textual data, eg, the politics of network and multi-plexity and the double ’embeddedness’ of SN – networks within networks. In the case of Beirut, sect/ religious networks also very important in understanding the networks of cultural production.

Will be undertaking dual mode of network analysis and then to explore the semiotics running behind these networks. So the interaction of politics and cultural production can be explored.

Weeknotes [21022014]

A picture of various draft word processed documents
In this last week, I have mainly been:

Sociability and networking

I’m currently analysing a couple of Twitter chat events aimed at learning professionals. The analysis will mainly be qualitative but to make sense of what are often a messy and chaotic events, I’m currently doing some pattern searches on the nature and functions of participants’ interactions. This image is of a social network analysis of both communities over a three month period. Now I really wasn’t expecting something like this – more that two distinct groups would emerge with a few boundary spanners. What I’m seeing is a densely networked professional community with few distinct clusters and stronger ties between the two event communities than a casual read through the event archives would have suggested.
Network ALL2_BCMore analysis is needed on the types of exchanges being seen but its an interesting image nonetheless.

Social network: knowledge and learning at work

Here are my slides from a workshop held for the University Forum for Human Resource Development (UHRD)

My talk was followed by Amy Woodgate talking about the University of Edinburgh‘s experience with MOOCs. There is a detailed report on the University’s first round of MOOCs available here. What surprised me, was the extent of the treatment of MOOCs as Open Education Resources  and the positive way the University was supporting other universities in using MOOC content for their own degree programme, other organisations in using MOOC resources for workplace learning and even schools using the MOOCs for classroom teaching. All in all, an inspiring talk and discussion.

Whether formal or informal, its the learning that counts

I liked Nick Shacklton-Jones’ post arguing that there’s no such thing as formal learning concluding that

My point, I suppose, is that if you have a good understanding of how learning works, you don’t have to fabricate mythical species of learning to explain what you see. There is just learning, and the way in which it happens in various contexts. The more you think about it, the sillier it seems – that we should categorise learning based on the convention in which it occurs. The same mechanism is at work, whatever the context.

Formal learning, as he is describing it, is really a task-based activity concerned with completion to a quality standard (assessment/ exams). By understanding learning as what it is, intentional and self-directed allows an almost complete reconfiguration of how learning is supported (not provided or delivered). It should be emphasised that learning is about learning ‘how’ to do something and so also, knowing where to find information/ knowledge and who to ask and much less acquiring knowledge.

For this reason, I think a research project on ‘Charting‘:

Charting is the process whereby an individual manages and optimises their interaction with the people and resources who (may) have a role in their learning and development.

is well worth watching – for its implications for work-based learning as well as for higher education.

Notes from Twitter and Microblogging: Political, Professional and Personal Practices. 10 April

These are notes from the Twitter and Micro-blogging conference at Lancaster University.  The full programme can be found on Lanyard. The Twitter hastag is #LUTwit

Introduction started from @JuliaGillen with the general acknowledgements, thanks and background to the conference. In particular, the conference emerged from the interests of the Linguistics dept in social media and some concerns of commercial capture of analysis of social media and companies striving towards linguistic analysis without really understanding what it is or might be.

Just going through the programme for the next couple of days.

First up is Lee Salter from University of the West of England  speaking at the Plenary on: online freedom and repressive law. His research  interests are in social media, journalism and protest movements. Author, with Janet Jones, of Digital Journalism.

His interest in SoMe is the relationship to trad journalism and paradoxes related to uses of SoMe and the responses form trad journalism and also from the state.

Twitter is “lots of different things to lots of different people” including as hub for reporting popular protests.

Seeking a middle way between journalist opposition to SoMe while also avoiding the hyperbole. Use of SoMe emerges from particular disasters of the Tsunami and the London bombings rising profile of twitter for news. This was cemented by the use of Twitter in reporting popular protests around the world providing news hours before broadcast news.

Criticisms of Twitter concern its lack of structure, fragmentation and incremental addition of information to fill the 24hour demand. Key criticism is that Twitter reconfigures relationship between journalist, audience and subjects (protestors).

Has Twitter changed communicative power relations and empower protestors or not. Journalists acting as gatekeepers and filters of news content as institutionalised relations of power. Argument that these relations are being undermined by SoMe – its immediacy and interactional nature. This includes that SoMe undermines the temporal structuring of the news cycles and so influence how news may be reported and by whom – so news comes form non-elite reporters. So disrupts temporality and in terms of power relations.

But is that correct? Influence on SoMe depends on the resource base of the reporter – that Twitter is used by a small minority who actually used Twitter and those that do are generally affluent (in UK) – while in US are more likely to be female and black/ hispanic and have fewer than 50 followers.

Study of Twitter use in Australian elections was dominated by established journalists with agenda reflecting traditional power relations. Online activists engaged in loosely coupled (competitive and fluid assemblages) relationships with traditional reporters. News continues to be dominated by small elites – business as usual.

The use of Twitter in news discourses is under-researched but research of BBC website and wiki news comments found commentary filtered to privilege the ‘middle ground’ – reinforcing the notion and assumption of traditional journalistic neutrality.

Traditional news providers integrated use of twitter as a linear narrative yet Twitter does not have a linear discursive structure.

In protest movements eg, Egypt, Tunisia, Syria seen as examples of SoMe in use of SoMe (albeit overrated) yet Bahrain ignored. SoMe used to explain what going on – to communicate to the outside world and bounce back through mainstream media. So media discourses integrated in a way that didn’t happen in Bahrain & Saudi Arabia.

Twitter influence reflects and replicates power of traditional media – Piers Morgan was the most popular (cited?) journalist on Twitter on the London riots.

Shown a couple of clips showing journalists engaging with and supportive of Arab Spring protestors yet dismissive of student protestors in London.

Moving on to why SoMe not shut down by authorities and suggesting that the internet is perceived as an ‘act of nature’ and “just there”! Lawrence Lessig argues on one hand have state regulation, on another is economic regulation and on another hands are norms (hegemony). So a regulatory regime occurs that means overt state regulation is less important. Cites the case of Paris Brown and Paul Chambers on the public private dichotomy breaking down in peoples minds yet the legal frameworks have failed to keep-up with changes in technology and practices. In particular, argues that e-communications are more stringently regulated in law than the traditional press, ie, for inappropriate use – but what is appropriate use of Twitter. Points to cases of people being imprisoned for incitement on SoMe.

Points out that for the London riots, alternative explanations of the riots and rioters fail to reach the mainstream media. The idea that SoMe transforms power relations is clearly questionable. Furthermore, that SoMe was more used in post-riot clean-ups rather than in the actual riots.

A further function of SoMe is its use by the police (in UK) for intelligence gathering and to use it to engage with protest “leadership” – even if reality is that there was no leadership while police continue to assume there ‘must be’!

Police use of SoMe in riots a combination of information, calls to stay calm, to seek information, to name and shame, to threaten rioters.

Overall points to emergence of Foucault notion of governmentality – that SoMe spaces are self governed.

Anonymous cited as a ‘proper’ cyber movement yet full of paradoxes: if anonymous, how can you be sure about anything they do; also against the mainstream while reliant on the mainstream as seek to influence that mainstream. Anonymous is a leaderless network that can only be understood if we set aside notions of centralisation [who or what is the actor here?]. But [unsurprisingly] such groups are excluded/ dismissed from the mainstream – as a discursive exclusion.

Twitter not address discursive exclusions and not part of the mainstream of news reporting and g=hegemonic aspects of news reporting has not really been challenged. SoMe normalised into the mainstream but that the law have failed t respond to these developments – see Leveson inquiry