Dissertation: Social Network Services positioning in an innovation ecosystem

The dissertation by Arash Hajikhani from LUT advances the existing research on innovation ecosystems by incorporating the soft aspects of innovation and studying Social Network Services (SNSs) as a complementarity within the innovation ecosystem.

Holistic view to improve innovation evaluation

In today's knowledge-based economies, it is generally accepted that innovations are integral to the foundation economic development, as well as one of the main causes for social and technical transitions. In an effort to evaluate and benchmark innovation, metrics and indicators have been designed to measure its various stages of development in order to gain insight into what is driving results.

In order to better comprehend the major stakeholders and driving forces of innovation, an ecosystem approach has recently begun to attract attention as a framework for studying innovation. The term "innovation ecosystem" is often employed to explain a large and diverse set of participants and resources essential to the success of any innovation.

Literature on innovation ecosystems emphasizes both the importance of a network of linkages between multiple actors and taking a holistic approach to include all players in the ecosystem. This is done to provide synergy, which has an effect on the overall outcome.


Social networking platforms provide opportunities for societal discussion
SNSs or social media platforms do not have a long history of existence in our societies but their fast evolution has created various opportunities and challenges. SNSs platforms (e.g. Twitter, Facebook) provide opportunities for mass communication and interaction, both of which mediate societal discussion.

SNSs platforms often have a network structure regarding the relations among its users which facilitates the growth of the network as well as the dissemination of the content. Often times the accumulation of interaction among users in SNSs is what is perceived (i.e. most liked or shared content) however the underlying factors such as content producer and type of content is the most important information yet to recognize.

Advancement in text analytics, natural language processing and machine learning models utilized on SNSs data to extract valuable insight which is crucial for evaluation of innovation and accurate comprehension of the innovation ecosystem. 

Evaluating public discourse and innovation

Hajikhani's thesis conceptually evaluates the features of SNS's data as an entity which represents public discourse or in other terms social capital. Furthermore, a systematic methodological framework has been adopted to transform SNS's data into units of analysis that enables innovation-oriented activities evaluation and benchmarking in various levels (firms, economies, societies).
These analyses resulted in exploring hidden layers of information embedded in SNS's data such as the role of content producer, content type and content quality in the overall interaction with SNS's participants.

The in-depth analysis of SNSs data revealed that user's interaction and information dissemination depends on the type of content (i.e. news, educational content, etc.) and the type of content producer (i.e. corporate announcements, governmental agency, etc.). Depending on the context where SNSs platforms is used for communication and dissemination of information (i.e. marketing campaign, startups activities or natural disaster), it is the most important step to distinguish among actors in SNSs, their interactions with other actors and accordingly their produced content.

In addition, the analysis of SNSs data on the topical level of discussions indicates their evolution overtime and the importance of actor's role in the topical evolution. The findings should help scientists and practitioners to engage with SNSs in a more confident manner when an ecosystem-oriented approach is taken to evaluate innovation.


Information about the dissertation

Arash Hajikhani, Master of Science in Technology, will defend his doctoral dissertation at Lappeenranta University of Technology on 5th October at 12.00 at the lecture room 2303. His dissertation is titled Understanding and leveraging the social network services in innovation ecosystems. Professor Pekka Kess, University of Oulu Finland will act as opponent. Professor Helinä Melkas of LUT will act as custos. Professor Jari Porras acted as the second supervisor.


The dissertation has been published in the Acta Universitatis Lappeenrantaensis research series number 811 of the university. ISBN 978-952-335-265-0, ISBN 978-952-335-266-7 (PDF), ISSN 1456-4491. The electronic version can be found from LUTPub-database http://urn.fi/URN:ISBN:978-952-335-266-7. A printed version of the dissertation may be purchased from the Aalef bookstore, tel. +358 44 744 5511, or at kirjakauppa@aalef.fi or online from the LUT Shop: https://lutshop.lut.fi/.

Further information
Arash Hajikhani, arash.hajikhani@lut.fi