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- 1. 1 Stuart Palmer(@s_palm ) Deakin University, Australia Characterizing the Interactions of a Multinational Engineering Services Company on Twitter
- 2. 2 Social media systems (SMS) For organisations: New means for communication & collaboration with many classes of external stakeholders Improve staff communication and collaboration Operationalize informal organizational networks A mechanism for implementing open innovation approaches
- 3. 3 Examples from engineering ? Engineering support and space flight operations control at NASA ? Sharing best-practice project management knowledge in a multinational petrochemical company ? Using profiles and activities of SMS users to identify knowledge domain experts ? A repository for knowledge in globally distributed technology development projects ? Risk and crisis communication in safety, health and environmental activities ? Professional networking opportunities for those seeking employment in the industry ? A timely professional learning channel ? A marketing channel for new products and ideas ? One source of ¡®big data¡¯ for improving manufacturing performance, including sustainability performance
- 4. 4 Engineering services organisations For marketing engineering services, SMSs allow the segmentation of audiences to a high level of granularity, and hence for brand messages to be highly focused Market intelligence for innovation and competition ¨C via gathering data from SMSs, potentially in combination with content interpretation methods such as natural language processing Engineering services companies have relied on ¡®social networks¡¯ long before the existence of SMSs ¨C however they offer new ways for engineers to share information, and companies can capitalize on this channel by the deliberate introduction of an organizational SMS Corporate responsibility (CR) reporting has traditionally been a one-way ¡®push¡¯ of information to stakeholders - SMSs provide an online channel for CR reporting that is potentially much more interactive
- 5. 5 Project aim Use publicly available data for analysis and visualisation to characterise the engagement of a multinational engineering services company on the Twitter SMS Specifically, using text analytics and visualization
- 6. 6 Method Ethics ¨C public data ruled exempt Weekly data collection 1/1/2016 to 30/6/2017 Tweets from and mentioning the organisation 3 sets of 6 months; separated into ¡®from¡¯ & ¡®to¡¯ Text analytics via KH Coder ¨C multidimensional scaling
- 7. 7 Twitter data set Date Tweets from Tweets to/about Total Jan-Jun 2016 844 1871 2715 Jul-Dec 2016 753 1786 2539 Jan-Jun 2017 360 3715 4075 Totals 1957 7372 9329
- 8. 8 MDS ¨C General features
- 9. 9 MDS ¨C ¡®from¡¯ Jan-Jun 2016
- 10. 10 MDS ¨C ¡®from¡¯ Jan-Jun 2016
- 11. 11 MDS ¨C ¡®from¡¯ Jan-Jun 2016
- 12. 12 MDS ¨C ¡®from¡¯ Jan-Jun 2016
- 13. 13 MDS ¨C ¡®to¡¯ Jan-Jun 2016__
- 14. 14 MDS ¨C ¡®to¡¯ Jan-Jun 2016__
- 15. 15 MDS ¨C ¡®to¡¯ Jan-Jun 2016__
- 16. 16 MDS ¨C ¡®to¡¯ Jan-Jun 2016__
- 17. 17 MDS ¨C Jul-Dec 2016 From To/About
- 18. 18 MDS ¨C Jul-Dec 2016 From To/About
- 19. 19 MDS ¨C Jan-Jun 2017 From To/About
- 20. 20 MDS ¨C Jan-Jun 2016 From To/About
- 21. 21 MDS ¨C Jan-Jun 2016 From To/About
- 22. 22 MDS ¨C Jul-Dec 2016 From To/About
- 23. 23 MDS ¨C Jan-Jun 2017 From To/About
- 24. 24 MDS ¨C Jan-Jun 2017 From To/About
- 25. 25 Conclusions Limited social media ¡®conversation¡¯ occurring The company is being mentioned on Twitter The company is tweeting about other topics Tweets from company down 2.5 times Tweets to/about company doubled Overall, 10 times as many mentions as tweets
- 26. 26 Conclusions Company largely using Twitter as a megaphone Twitter mentions are ephemeral Must be captured in near real-time Method piloted here for monitoring the large- scale ¡®conversations¡¯ occurring on Twitter
- 27. 27 Thank you for your time