Social Media Cloud Contact Center Using Chatbots

  • George SuciuEmail author
  • Adrian Pasat
  • Teodora Ușurelu
  • Eduard-Cristian Popovici
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 283)


The latest technologies advancement in NLP (Natural Language Processing) solution allows developing innovative tools that enrich customer experience with products and services. Contact Center environments gradually adopted real-time analytics solutions, and latest research is focusing on how to integrate social media channels. Based on the work made in SoMeDi and Speech2Processes projects, we propose an innovative chatbot platform that integrates data mining and sentiment analysis technologies. The aim is to offer insight into customer preferences by using DII (Digital Interaction Intelligence) and assist in mitigating several know issues in Contact Center environments.


Chatbot Artificial intelligence DII NLP Machine learning 



This work was supported by a grant of the Ministry of Innovation and Research, UEFISCDI, project number 5 Sol/2017 ToR-SIM within PNCDI III and partially funded by UEFISCDI Romania under grants Speech2Process and SoMeDi projects, and by European Union’s Horizon 2020 research and innovation program under grant agreement No. 643963 (SWITCH project).


  1. 1.
    Castro, D., New, J.: The promise of artificial intelligence. Center for Data Innovation (2016)Google Scholar
  2. 2.
    McCormick, J., Little, C.: Optimize customer experiences with digital intelligence. In Forrester Report, The Digital Intelligence Playbook (2016)Google Scholar
  3. 3.
    Suciu, G., Anwar, M., Conu, R.: Social media and digital interactions using cloud services for orienting young people in their careers. ELSE Conf. 2, 419–427 (2017)Google Scholar
  4. 4.
    Shinde, S., Mangrule, R.A.: Discovery of frequent itemset using higen miner with multiple taxonomies. Int. J. Curr. Trends in Eng. Res. 2(6), 373–383 (2016)Google Scholar
  5. 5.
    Wu, Y., Wu, W., Li, Z., Zhou, M.: Response selection with topic clues for retrieval-based chatbots. In: Symposium for Advancement of Artificial Intelligence, pp. 1–8 (2016)Google Scholar
  6. 6.
    Lai, S., Xu, L., Liu, K., Zhao, J.: Recurrent convolutional neural networks for text classification. AAAI 333, 2267–2273 (2015)Google Scholar
  7. 7.
    Behera, B.: Chappie-a semi-automatic intelligent chatbot. In LCPST, pp. 1–5 (2016)Google Scholar
  8. 8.
    LUKA Artificial Intelligence 12 Jun 2017.
  9. 9.
    LARK Care Continuum Platform 12 Jun 2017.
  10. 10.
    Penny personal finance coach 12 Jun 2017.
  11. 11.
    Patil, A., Marimuthu, K., Niranchana, R.: Comparative study of cloud platforms to develop a Chatbot. Int. J. Eng. Technol. 6(3), 57–61 (2017)CrossRefGoogle Scholar
  12. 12.
    Language Understanding Intelligence 12 Jun 2017.
  13. 13.
    Szőts, M., Halmay, E., Gergely, T., Suciu, G., Cheveresan, R.: Semantics driven intelligent front-end. In: SpeD Conference, pp. 1–4 (2017)Google Scholar
  14. 14.
    Baruah, T.D.: Effectiveness of social media as a tool of communication and its potential for technology enabled connections: a micro-level study. Int. J. Sci. Res. Publ. 2(5), 1–10 (2012)Google Scholar
  15. 15.
    Aral, S., Dellarocas, C., Godes, D.: Social media and business transformation: a framework for research. Inf. Syst. Res. 24(1), 3–13 (2013)CrossRefGoogle Scholar
  16. 16.
    Kaplan, A.M., Haenlein, M.: Users of the world, unite! the challenges and opportunities of social media. Bus. Horizons 53(1), 59–68 (2010)CrossRefGoogle Scholar
  17. 17.
    Houwens, B.: Machine Learning and UX. In Directed Simplicity, pp. 1–8 (2017)Google Scholar
  18. 18.
    Shaikh, F.: The benefits of new online (digital) technologies on business: understanding the impact of digital. In Digital Entrepreneurship and Global Innovation, pp. 1–4 (2016)Google Scholar
  19. 19.
    Stelzner, M.A.: Social media marketing industry report. how marketers are using social media to grow their businesses. In: Social Media Examiner (2016)Google Scholar
  20. 20.
    Oracle, An Oracle Best Practice Guide: Best Practices for Improving First-Contact Resolution in the Contact Center (2012)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  • George Suciu
    • 1
    • 2
    Email author
  • Adrian Pasat
    • 1
  • Teodora Ușurelu
    • 1
  • Eduard-Cristian Popovici
    • 2
  1. 1.Research & Development DepartmentBeia Consult InternationalBucharestRomania
  2. 2.ETTI FacultyUniversity POLITEHNICA of BucharestBucharestRomania

Personalised recommendations