When a social network knows it is being watched does it change?


There is tremendous value in analysing social networks, both internally to an organisation, and looking at the social networks of the organisation’s customers, suppliers, industry influencers etc. but what happens when that community becomes aware that their publications and interactions are being analysed?

I asked this question at Social Data Week ’13 in London  and the panel’s answer was that it did: you can already observe people taking advantage of this in expecting some sort of reward for following, or otherwise being associated with, organisations. This sounds fairly innocuous but I am more concerned about observing networks inside the organisation.

Think about the following scenario: an organisation analyses IMs to gauge sentiment and presents this information by department; one department noticeably has a lot of negative sentiment compared to the others; the department’s manager is advised of this and asked to devise and implement a plan to improve the situation. What could they decide to do, the three options are:

1         The right thing: find the root causes and address them

2         The lazy thing: don’t do anything, hope it improves

3         The wrong thing: tell members of the department the communications are being monitored and not to use negative language

I have actually observed the wrong thing being done when it comes to staff surveys (which amongst other things are trying to gauge staff sentiment about the organisation): the manager of the department let it be known they did not want to see negative ratings of management in the survey, presumably because the results of the survey had some bearing on their bonus. I fear the same thing would happen if social network analysis and/or sentiment analysis were being used.

Another option an organisation has is to use surveys to build a picture of the social network (I’ve recently exchanged some views with TECI who take this approach). In this case its clear that the organisation is collecting the data but I wonder how accurate this is; I think people may either not answer entirely honestly or simply forget about certain connections in their network as they don’t seem important (but could be very important in the overall network). I’d love to know if anyone has any studies that compare networks derived from surveys with those derived from communications data. My guess is doing both and combining the results would give the most accuracy.

So if an organisation does want to use communications data for SNA what should it do? Having thought about this I think the answer if to firstly baseline the communications data and then announce that the organisation has such an intent (assuring staff that it will be analysed anonymously) and finally observe the communications data to see if there is a change from the baseline. The next step depends on the result: if there is very little change then it’s probably OK to carry on but if there is a noticeable change then this is telling the organisation something and it needs to understand why there was a change before proceeding.

Does anyone know of any studies, or have any experience of, social networks changing if they become aware they are observed?


4 thoughts on “When a social network knows it is being watched does it change?

  1. Chris Copland

    Great post Robert!

    I’ve always been fascinated by the ‘observer effect’ on social networks, particularly internal networks, and you raise some interesting issues relating to this. Problems can be manifested in various ways, either through people trying to ‘game’ the system (I’ve also seen this happen with employee surveys) or worse case it can negatively impact on usage and adoption of an internal social/collaborative platform (in effect killing off the very thing you’re trying to create – open, honest conversation, people ‘working out loud’ etc).

    I think any analysis of internal social data needs to be handled with care. This means being very sensitive to issues such as privacy and anonymity, as you highlight, and being clear and open with employees about why and how this is being done. Ideally data should be shared back with the network, and should be used to help drive improvements for both users/employees and the overall organisation.

    I’m not aware of any specific academic research into the effect of observation on social networks, but this is a good summary of the traditional ‘Hawthorne effect’ (together with the Pygmalion effect and the Placebo effects) which I believe has application to the issues you’re raising with regards to social network analysis http://www.psy.gla.ac.uk/~steve/hawth.html

    Looking forward to your next post on this fascinating topic!


    1. Robert Gimeno Post author

      Thanks for the reply and the link. From reading that it does seem somewhat inconclusive but I understand the issues a little more now.

  2. Laurence Lock Lee

    We have been conducting internal SNA projects for over a decade now and this questions is asked all the time. No doubt that once a survey is repeated and people know how the results get used they may be more thoughtful on how they respond to a second round. The main point is whether this might invalidate the second round results or not. While I have no scientific proof, we think this is minimised by our practice of virtually only relying on the ‘in-degree’ or inward nomination measure. 90% of our analytics are drawn from in-degree measures. So its not about who you nominate, but who nominates you. This is harder to game. You would have to virtually run an election campaign to impact this….and we haven’t seen any evidence of this being done. In fact those that think that nominating a lot of people will make them look better, could have the opposite effect. What would you think of someone who nominated 100 connections but only received 2 themselves?

    There is scientific support for preferring the in-degree measure. It is the most robust in terms of differing sample sizes and sample completion rates. If you want to read more on this have a look at:
    Costenbader E, Valente TW (2003) The stability of centrality measures when networks are sampled. Social Networks 25(4):283–307
    as an example of this…there are several more studies on this that pretty much support the use on indegree as the most reliable SNA measure.

    1. Robert Gimeno Post author

      Laurence, thanks for sharing your insights, I can see how the in-degree would be the best measure for a survey approach but I wonder if people forget, or perhaps ignore, colleagues of a lower grade?


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