In 2016, Brexit and the election of Donald Trump resolutely demonstrated the political power of social media. David Beer asks how we might better understand ‘influence’ in the machinations of social media, and how this influence might be harnessed by those in, or seeking, office

Beer, David

LSE Research Online

1/6/2017Measuring and engineering inﬂuence on social media: what doesthis mean for political power?blogs.lse.ac.uk/europpblog/2017/01/06/measuring-and-engineering-inﬂuence-on-social-media/In 2016, Brexit and the election of Donald Trump resolutely demonstrated the political power ofsocial media. David Beer asks how we might better understand ‘inﬂuence’ in the machinations ofsocial media, and how this inﬂuence might be harnessed by those in, or seeking, oﬃce.One of the most interesting features of the new types of social media analytics that are emerging isthe growing possibilities they oﬀer for measuring inﬂuence. It has become possible to see whosevoices are getting heard above the din of decentralised media. Being able to capture the reactionsof people enables a much more detailed encounter with inﬂuence than was previously possible.The research conducted for this project and its conclusions, bring to mind the recent commentaries on the role ofsocial media in both the Brexit referendum and US election results. What is often missing in these debates about‘post-truth’ politics and social media ‘news’ circulations is that inﬂuence is now something that can be measured andtracked – this aﬀords a whole new knowledge base from which inﬂuence can then be exercised and engineered.The data produced as a by-product of social media use have made it possible to see who is inﬂuential and in whatways. Of these inﬂuence measures Klout is probably the best known, but it is far from the only metric. Klout, whichpresents itself as a self-training tool, gives a score of how inﬂuential our social media voices are. But the measuresgo beyond this. Indeed, the software package I used in my (admittedly small-scale) project incorporated Kloutamongst a range of other inﬂuence measures. Using a slider you could decide which measures you’d like toprioritise in understanding inﬂuence.Perhaps the most telling measure was that of ‘ampliﬁcation’, which was a measure of the generation of activity in theform of responses and shares. This measure can be used to assess the reaction and activity that individuals canprovoke. In other words, having inﬂuence is not just about the numbers of followers or friends, it is about reaction. Itis possible to follow the traces to see what happens to that content and where it ends up.Another measure, ‘true reach’, similarly focuses on how broad an audience the content stretched across – not justdirectly but after it is shared and re-shared.  Alongside this, ‘network score’ shows how inﬂuential your engagednetwork is. Here new types of data from social media have combined with new types of analytics to reveal theimplicit hierarchies within social media’s apparently ﬂat networks.1/3Image credit: geralt (CC0 public domain) via PixabayThe result of all this is that it is possible to understand inﬂuence in a way that couldn’t previously have beenimagined. This is powerful information for those who pursue inﬂuence. When thinking about social media analyticswe often think about how ‘buzz’ is measured or how ‘sentiment’ can be followed. Sentiment and buzz are importantand they are now active ingredients in the unfolding of more knowing and analytical social processes. What tends toget much less attention is ‘inﬂuence’, and what it means if we can measure and follow inﬂuence either in real-time orin relation to previous events.This new knowledge about inﬂuence can then be utilised in two ways. First, inﬂuential actors, now identiﬁed, canbecome targets for assisting in getting points heard. So, it might be that inﬂuential people are asked or induced toshare content to maximise its impact. This is a kind of proxy inﬂuence. It is a little like when brands try to get trend-makers to wear their shoes or clothes in the street – or post pictures of them on Instagram.Second, and more crucially, once inﬂuence is understood through social media analytics the actions that createinﬂuence can be mimicked or replicated – maybe not perfectly replicated, but at least partially so. Knowing andunderstanding inﬂuence means that it can potentially be engineered. Passing messages to trend-makers requiresthe involvement of the trend-maker, but understanding how inﬂuence itself is achieved and exercised means that itcan be built, developed and honed.Having knowledge about the machinations of inﬂuence is not just a way of recording what is going on, it also makesit possible to craft and build inﬂuence in these spaces. Once the how of inﬂuencing is known, then it becomessomething that can be designed into social media use. For this reason, when we think about the inﬂuence that socialmedia feeds had upon political outcomes, like the election of Donald Trump, we should be thinking about the waythat analytics can be used to monitor, inform and engineer that inﬂuence.We know that Trump had a data analytics team that was trying to target and respond to social media data. Analyticsare now embedded in politics. My own project was very modest in scale, but imagine what might be known by thosewith much larger budgets. Understanding how to get ampliﬁed is a key part of how these tools can be used. Theseanalytic software are designed to assist with the modiﬁcation and shaping of behaviour and to help exploit thepossibilities the data reveal.2/3The new types of knowledge that they produce about inﬂuence are likely to be powerful in politics, especially aspeople who want to be inﬂuential deploy this knowledge to pursue or exercise power. Like anything else, onceinﬂuence can be measured and traced, behaviours change and patterns of inﬂuence are themselves likely to bealtered. Perhaps we have been seeing how a new type of knowledge about inﬂuence is already allowing this tohappen.Please read our comments policy before commenting .Note: This piece originally appeared on the LSE British Politics and Policy blog. It is based on the author’s article,‘Using Social Media Data Aggregators to Do Social Research ’, published in Sociological Research Online (DOI:10.5153/sro.2618). The article gives the views of the author, and not the position of EUROPP – European Politicsand Policy, nor of the London School of Economics. _________________________________About the authorDavid Beer – University of YorkDavid Beer is Reader in Sociology at the University of York. His most recent book is Metric Power.His earlier book Popular Culture and New Media: The Politics of Circulation was recently publishedin paperback.3/3

Measuring and engineering influence on social media: what does this mean for political power?

In 2016, the Brexit vote and the election of Donald Trump resolutely demonstrated the political power of social media. David Beer asks how we might better understand ‘influence’ in the machinations of social media, and how this influence might be harnessed by those in, or seeking, office

12/19/2016Measuring and engineering influence on social media: what doesthis mean for political power?blogs.lse.ac.uk/impactofsocialsciences/2016/12/19/measuring-and-engineering-influence-on-social-media-what-does-this-mean-for-political-power/In 2016, the Brexit vote and the election of Donald Trump resolutely demonstrated the politicalpower of social media. David Beer asks how we might better understand ‘influence’ in themachinations of social media, and how this influence might be harnessed by those in, or seeking,office.One of the most interesting features of the new types of social media analytics that are emerging isthe growing possibilities they offer for measuring influence. It has become possible to see whosevoices are getting heard above the din of decentralised media. Being able to capture the reactionsof people enables a much more detailed encounter with influence than was previously possible. The researchconducted for this project and its conclusions, bring to mind the recent commentaries on the role of social media inboth the Brexit referendum and US election results. What is often missing in these debates about ‘post-truth’ politicsand social media ‘news’ circulations is that influence is now something that can be measured and tracked – thisaffords a whole new knowledge base from which influence can then be exercised and engineered.The data produced as a by-product of social media use have made it possible to see who is influential and in whatways. Of these influence measures Klout is probably the best known, but it is far from the only metric. Klout, whichpresents itself as a self-training tool, gives a score of how influential our social media voices are. But the measuresgo beyond this. Indeed, the software package I used in my (admittedly small-scale) project incorporated Kloutamongst a range of other influence measures. Using a slider you could decide which measures you’d like toprioritise in understanding influence. Perhaps the most telling measure was that of ‘amplification’, which was ameasure of the generation of activity in the form of responses and shares. This measure can be used to assess thereaction and activity that individuals can provoke. In other words, having influence is not just about the numbers offollowers or friends, it is about reaction. It is possible to follow the traces to see what happens to that content andwhere it ends up. Another measure, ‘true reach’, similarly focuses on how broad an audience the content stretchedacross – not just directly but after it is shared and re-shared.  Alongside this, ‘network score’ shows how influentialyour engaged network is. Here new types of data from social media have combined with new types of analytics toreveal the implicit hierarchies within social media’s apparently flat networks.1/3Image credit: geralt (CC0 public domain) via PixabayThe result of all this is that it is possible to understand influence in a way that couldn’t previously have beenimagined. This is powerful information for those who pursue influence. When thinking about social media analyticswe often think about how ‘buzz’ is measured or how ‘sentiment’ can be followed. Sentiment and buzz are importantand they are now active ingredients in the unfolding of more knowing and analytical social processes. What tends toget much less attention is ‘influence’, and what it means if we can measure and follow influence either in real-time orin relation to previous events.This new knowledge about influence can then be utilised in two ways. First, influential actors, now identified, canbecome targets for assisting in getting points heard. So, it might be that influential people are asked or induced toshare content to maximise its impact. This is a kind of proxy influence. It is a little like when brands try to get trend-makers to wear their shoes or clothes in the street – or post pictures of them on Instagram. Second, and morecrucially, once influence is understood through social media analytics the actions that create influence can bemimicked or replicated – maybe not perfectly replicated, but at least partially so. Knowing and understandinginfluence means that it can potentially be engineered. Passing messages to trend-makers requires the involvementof the trend-maker, but understanding how influence itself is achieved and exercised means that it can be built,developed and honed.Having knowledge about the machinations of influence is not just a way of recording what is going on, it also makesit possible to craft and build influence in these spaces. Once the how of influencing is known, then it becomessomething that can be designed into social media use. For this reason, when we think about the influence that socialmedia feeds had upon political outcomes, like the election of Donald Trump, we should be thinking about the waythat analytics can be used to monitor, inform and engineer that influence. We know that Trump had a data analyticsteam that was trying to target and respond to social media data. Analytics are now embedded in politics. My ownproject was very modest in scale, but imagine what might be known by those with much larger budgets.Understanding how to get amplified is a key part of how these tools can be used. These analytic software aredesigned to assist with the modification and shaping of behaviour and to help exploit the possibilities the data reveal.The new types of knowledge that they produce about influence are likely to be powerful in politics, especially aspeople who want to be influential deploy this knowledge to pursue or exercise power. Like anything else, onceinfluence can be measured and traced, behaviours change and patterns of influence are themselves likely to be2/3altered. Perhaps we have been seeing how a new type of knowledge about influence is already allowing this tohappen.This piece originally appeared on the LSE British Politics and Policy blog and is published under a CC BY-NC-ND3.0 license. It is based on the author’s article, ‘Using Social Media Data Aggregators to Do Social Research ’,published in Sociological Research Online (DOI: 10.5153/sro.2618).This article gives the views of the author, and not the position of the LSE Impact Blog, nor of the London School ofEconomics. Please review our comments policy if you have any concerns on posting a comment below.About the authorDavid Beer is Reader in Sociology at the University of York. His most recent book is Metric Power. His earlier bookPopular Culture and New Media: The Politics of Circulation was recently published in paperback.Copyright © The Author (or The Authors) - Unless otherwise stated, this work is licensed under a CreativeCommons Attribution Unported 3.0 License.3/3

Measuring and engineering influence on social media: what does this mean for political power?

Abstract

Similar works

Full text

Available Versions

LSE Research Online

LSE Research Online