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Insights into our society – what we can learn from Social Media Analytics (SMA)

Insights into our society – what we can learn from Social Media Analytics (SMA)

Social media communication now has an enormous influence on our day-to-day lives. This particularly concerns professional and private decision-making processes made possible by new forms of public communication with decisions to buy or choose something, for example. Phenomena such as fake news, social bots or putative filter bubbles raise the issue of how we can ensure that all people have the chance to access the same information. So it has become imperative to examine such phenomena with the aid of complex analytical systems.

Professor Stefan Stieglitz from the university of Duisburg-Essen and Karsten Kraume, CRm Expert at Bertelsmann, talk about the significance, application options and future prospects for Social Media Analytics (SMA) here.

Mr Kraume, fake news, rumours and harmful bots that are spreading about on social media platforms jeopardise the integrity of companies and individuals – at least in the way they are perceived by the public. How serious are such phenomena?

Karsten Kraume: These phenomena are real and, consequently, should be taken seriously – both in the public and the private sector. As opinion makers in the social media can have a long-term influence on companies’ brand reputations, for example. At the same time these developments also have an effect at an operative level, as social media ensures that consumers have gained considerably more power. It gives them the opportunity to share their opinions about a product or service online with a very large number of people. This can have both a positive or a negative effect on a brand. Customers can express themselves positively, for example, so the company can profit from this if the online posting reaches a large audience. Or they can express themselves negatively and the company is then obliged to take measures to ensure that any negative effects of such posts are kept to a minimum. There is a wide range of examples for both cases. The “United Breaks Guitars” song, for example, by the Canadian musician, Dave Carroll, has so far reached a total of 18.5 million clicks on Youtube (as of December 2019). In the song, Carroll explained how his guitar was damaged in the baggage handling process during a United Airlines flight and criticised the customer service of this US-American airline. However the customers express themselves online, companies should show an interest in managing these discussions in the social media.

How can companies use their customer service departments to deal with such challenges?

Karsten Kraume: Just as in other areas of customer service, there are various options here. Some brands have decided that social channels are part of their company’s core expertise and handle their customer service internally through social media. Others decide in favour of outsourcing this task and assign their social media communication to strategic partners. There is also a hybrid approach where the value creation chain is considered, for example. This combines social analytics, social sales and content moderation among other aspects. As a leading BPS provider in Europe, and with a portfolio that extends from voice to non-voice channels, we at Arvato offer a range of different variations from end-to-end service right through to individual services. On balance, it is always important to offer a fully-integrated customer journey across all (social) channels – regardless of whether the customer communication is carried out internally or through an outsourced service provider and regardless of whether it is carried out by a person or a bot.

Mr Stieglitz, often social media leads to an information overload. What exactly is social media analytics and how can it help reduce the complexity of the data generated by social media?

Stefan Stieglitz: Basically our SMA approach covers four steps: data capture, data collection, data preparation and data analysis. In this process it is important to be aware of the peculiarities of the platform that is being analysed. We use SMA to determine the identification of various user roles and their influence on the communication and dissemination of content on the social web. Influencers and opinion makers, for example, can be identified through a social network analysis. By analysing the follower network of such a person, the reach of their messages can be determined. A ‘sentiment analysis’ is further method that is deployed within an SMA process. This can be used to determine the prevailing mood or opinion of a user or user group towards a particular message or person. Further potentials for development in the area of SMA come from machine learning and artificial intelligence approaches.

One of the areas of application for SMA is in crisis management. How can research into disaster management organisations, for example, help to meet the challenges that the use of social media brings with it in crisis situations?

Stefan Stieglitz: Social media platforms are indispensable communication channels in crisis situations today. Virtually all groups in society – from individual people, emergency management authorities and NGOs right through to the media – use social platforms to find and exchange information in such situations. In most cases people use social media to share their experience or knowledge for the purposes of organising help or providing emotional support. Disaster management organisations use social media to make reliable information available, express warnings and get into contact with the public. The biggest challenge for everyone involved in communication is to keep track of things when too much information is on offer. Finding out which information is consistent with reality is a crucial task here. This is where research can support us in recognising patterns that arise again and again in communication about catastrophes. This knowledge can then help the people involved to filter information more effectively and develop appropriate strategies for its dissemination, along with the involvement of the users in its proper communication.

Mr Kraume, experts and companies can expect other results from the implementation of SMA than researchers who pursue rather more theoretical questions. What can industry and science learn from each other through the analysis of social media data?

Karsten Kraume: The interaction can be advantageous for both parties. That’s something we have already experienced several times in the past. On the one hand, industry brings with it some relevant areas of application and can ensure that the research is applicable in practice. On the other hand, any new methods and algorithms that are developed in an academic environment can enrich the range of solutions that companies can offer. In the past we have got together with research institutions in various programmes, such as in the RISE_BPM,  a project promoted by the EU concerned with the future perspectives for Business Process Management (BPM). The focus here is on the four areas of Big Data, Real Time Computing, Smart Devices and Social Media. In another case we have taken a look specifically at social media in aviation .

What are the objectives of RISE_SMA, Mr Stieglitz, and how do you want to achieve them?

Stefan Stieglitz: RISE_SMA forms a cross-disciplinary and international network that brings together some excellent scientists and experts with practical experience to address the area of Social Media Analytics. Our objective is to give them the opportunity to exchange their knowledge and develop solutions for current challenges in areas such as political communication or disaster management this way. We use advanced theoretical approaches and methods for analysing social media data and concern ourselves above all with two areas. These are the impact of social media and its evaluation on society and crisis communication. Not just methods should be improved and patterns researched, however, specific solutions should also be developed. The project will begin in January 2019 and run over a period of four years.

Mr Kraume, what will the role of Arvato CRM Solutions be in the RISE_SMA project?

Karsten Kraume: Social media channels are already of special significance for us. Demand for it is growing both in the new digital business and in our core business. People and artificial intelligence are working closely together with us. That is how we drive forward our digital innovation. RISE_SMA complements our efforts – and we will be closely following the research projects and helping to shape them as part of our work on the advisory board.

With a view to the future, what in your opinion will be the role of SMA in five to ten years’ time?

Karsten Kraume: The significance of the social channels will have advanced even further compared with today. Automation will be playing a significant role. That’s why it is so important with RISE_SMA and other scientific initiatives that we work together with a strong practical approach – such as in the Social Media Competence centre at the European Research Centre for Information Systems (ERCIS) or at the Confederation of Laboratories for Artificial Intelligence in Europe (CLAIRE) . Together we will be researching and shaping where things will go with social channels in the future.

Stefan Stieglitz is Professor and Head of the Research Group for Professional Communication in Electronic Media / Social Media at the University of Duisburg-Essen. His work has been published in such well-known journals as the Journal of Management Information Systems, Business & Information Systems Engineering, in the International Journal of Information Management and in MISQe. In his research he examines Social Media Analytics in various areas such as business, politics and crisis communication.

Karsten Kraume is CRM Expert at Bertelsmann and a member of the Advisory Board at the European Research Centre for Information Systems (ERCIS) as well as at research programmes such as Business Process Management RISE and RISE Social Media Analytics. He is also active as general manager on the Social Media Analytics Competence Centre.

Author: Editorial team Future. Customer.
Image: © ra2 studio – AdobeStock

Tags for this article Customer Journey (20) Customer Management (34) Digitization (167) Social Analytics (2) Social Media (22)


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