sociology – Page 2 – Data Big and Small

Sociology in 2014: rediscovering methods

I was back last week from the annual conference of British Sociological Association (BSA) in Leeds, and as usual, I try to put down my impressions as long as they’re still fresh in my mind. I wasn’t very quick, though, and the BSA’s members newsletter has already come out with comments and short reports about the plenaries, the prizes awarded, and the conference overall. While the conference is described as having been “very vibrant and sociable”, with “exciting conversations” during the breaks and a “diverse mixture of topics” that “reflected the breadth of interests”. My own feelings, I confess, are a bit more mixed.

In 2012, the BSA conference was followed by a lively debate after an article, by Aditya Chakrabortty on the Guardian, where he complained about the discipline’s lack of engagement with the financial crisis. He pointed to the BSA press releases featuring research on “older bodybuilders”, and to time devoted to the “holistic massage industry” at the conference, as evidence of what he saw as a retreat from public space. The BSA took the criticism very seriously and, apart from responding to the Guardian, put in place a massive effort to encourage public engagement. The 2013 conference was entitled “Engaging Sociology” and many sessions were dedicated to showing that the profession means it. Confrontation and comparison with economics was open and clear. A major project on social class was presented with all honours. The Sociology journal released a call for papers for a special issue to “Sociology and the Global Economic Crisis”.

This year, the “Changing Society” title aimed to stress continuity with last year’s efforts; yet it seems to me that we are back to business as usual. I had the impression that many paper presentations were on topics similar to the body builders and massage that Chakrabortty talked about. That’s why, as I said, my feelings are mixed.

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Qualitative networks

Social Network Analysis (SNA) is booming, and many think it’s because of internet networks and big data. Yet social networks themselves are not new: people have always formed ties to one another, and online platforms such as Facebook, Twitter and LinkedIn only offer channels for networked interactions to occur. Counts and fancy visualisations of myriad likes and shares do not tell the whole story either: networks are primarily about exploring how ties connect us as individuals and as organisations or groups, and how our social relationships affect our lives and behaviours.

In this sense, smaller studies can still have much to teach us. These include not only quantitative, but also qualitative approaches. “Social” networks involve a world of meanings, feelings, relationships, attractions, dependencies, which have traditionally been at the heart of qualitative research and are amenable to a mixed-methods approach.

In this perspective, with the Social Network Analysis Group of the British Sociological Association (BSA-SNAG), I am organising a one-day small conference on “Mixed Methods Approaches to Social Network Analysis”, exploring how the combination of SNA and qualitative methods can enrich and deepen our understanding of network content in conjunction with network structure. The event will take place on 12 May 2014 at Middlesex University, London, and the programme is available here; to register online (deadline 30 April!) click here.

Whose fantasy are you living in? Your employer’s or Mark Zuckerberg’s?

A now classical result of the sociology of social networks is the distinction between formal social structures defined by kinship, inherited hierarchy or companies’ organisational charts, and informal structures arising from nets of friendship, trust, solidarity, similarities and dissimilarities. As far back as 1954, John A. Barnes (who incidentally, is credited with coining the wording ‘social networks’) in a renowned study of a small community of fishers in a Norwegian parish demonstrated that exogenously defined positions such as those arising from political administration, economic activity or family are insufficient to explain the social structure of the community, which largely depends on less codified relationships of friendship and acquaintance. In organisational studies, it appeared that the formal chart of a company and the actual networks of advice, trust or communication of members may differ widely, and surveys aimed at eliciting network ties (with ‘name generators’ for example) became a privileged means to bring to light the ‘company behind the chart‘ (Krackhardt & Hanson 1993) and to make ‘invisible work visible‘ (Cross, Parker & Borgatti 2002). Social network scholars advised managers on how, by using employee questionnaires, they could generate network maps and get to the root of many organisational problems. Another major finding was about the emergence of informal roles – the leader, the deviant, the broker – and their important contribution to driving the behaviours and outcomes of human groups, beyond all prescribed, formal authorities (Johnson, Boster & Palinkas 2003).

The formal chart of a company and the network obtained by asking each employee, “With whom do you discuss work-related issues?” Central individuals (who receive most nominations) are NOT the formal leaders.

The research and consultancy activity that built on these ideas had a strong impact on organisational culture worldwide, especially as companies tended to flatten and rely on teams and cross-divisional, project-based work, so that managers’ authority mattered less and understanding these informal networks became a potential key for success. Many would admit today that the organisational chart is the fantasy of the employer, not an actionable tool, and even less so a reliable reflection of reality. But then, what are the advice, trust, and communication networks mapped by the researcher – shouldn’t we say they are the fantasy of the sociologist? These networks are built from questionnaires and therefore rely on the subjective responses of participants; and it is well known in the area of survey design research, that question wording orients responses, that different cultures and groups tend to interpret questions differently, and that people may give biased answers due to forgetting, deliberate concealing of sensitive information, ambiguity of definitions, and diversity in perceptions. The survey is the traditionally primary tool of investigation of the social networks scholar, but brings with it its limitations and distortions.

One may think that the formal organisational chart and the informal advice (or trust or communication) network are just two different ways of construing social structure and objectivating it. They are informed by different political and epistemological orientations: those of (old-style) employers for the former, those of social researchers (and perhaps enlightened employers) for the latter. The resulting formal-informal dichotomy would then be the result of a cleavage between two competing approaches to the management of organisations (and more generally of human groups or communities), one more hierarchical and functional, the other flatter and more collaborative.

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Network data, new and old: from informal ties to formal networks

Network data are among those that are changing fastest these days. When I say I study social networks, people almost automatically think of Facebook or Twitter –without necessarily realizing that networks have been around for, well, the whole history of humanity, long before the internet. Networks are just systems of social relationships, and as such, they can exist in any social context — the family, school, workplace, village, church, leisure club, and so forth. Social scientists started mapping and analysing networks as early as the 1930s. But people didn’t think of their social relationships as “networks” and didn’t always see themselves as “networkers” even if they did invest a lot in their relationships, were aware of them, and cared about them. The term, and the systemic configuration, were just not familiar. There was something inherently informal and implicit about social ties.

What has changed with Facebook and its homologues, is that the network metaphor has become explicit. People are now accustomed to talking about “networks”, and think in systemic terms, seeing their own relationships as part of a more global structure. Network ties have become formal — you have to make a clear choice and action when you add a “friend” on Facebook, or “follow” someone on Twitter; you will have a list of your friends/followers/followees (whatever the specific terminology is) and monitor changes in this list. You know who the friends of your friends are, and can keep track of how many people viewed your profile /included you in their “lists” / mentioned you in their Tweets. Now, everyone knows what networks are –so if you are a social network researcher and conduct a survey like in the old days, you won’t fear your respondents may misunderstand. In fact, you may not even need to do a survey at all –the formal nature of online ties, digitally recorded and stored, makes it possible to retrieve your network information automatically. You can just mine network tie data from Facebook, Twitter, or whatever service your target populations happen to be using.

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#bigdataBL

On Friday last week, the British Sociological Association (BSA) held an event on “The Challenge of Big Data” at the British Library. It was interesting, stimulating and relevant – I was particularly impressed by the involvement of participants and the very intense live-tweeting, never so lively at a BSA event! And people were particularly friendly and talkative both on their keyboards and at the coffee tables… so in honour of all this, I am choosing the hashtag of the day #bigdataBL as title here.

(Visualisation: http://www.digitalcoeliac.com/)

Some highlights:

The designation of “big data” is from industry, not (social) science, said a speaker at the very beginning. And it is known to be fuzzy. Yet it becomes a relevant object of scientific inquiry in that it is bound to affect society, democracy, the economy and, well, social science.
Big-data practices change people’s perception of data production and use. Ordinary people are now increasingly aware that a growing range of their actions and activities are being digitally recorded and stored. Data are now a recognized social object.
Big data needs to be understood in the context of new forms of value production.
So, social scientists need to take note (and this was the intended motivation of the whole event). The complication is that Big Data matter for social science in two different ways. First, they are an object of study in themselves – what are their implications for, say, inequalities, democratic participation, the distribution of wealth. Second, they offer new methods to be exploited to gain insight into a wide range of (traditional and new) social phenomena, such as consumer behaviours (think of Tesco supermarket sales data).
Put differently, if you want to understand the world as it is now, you need to understand how information is created, used and stored – that’s what the Big Data business is all about, both for social scientists and for industry actors.

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