05 July 2024 | 8:26
Jiwat Ram

Sentiment analysis for project stakeholder management

The applications of natural language processing (NLP) for business use are growing rapidly. It is estimated that the market for the use of NLP for application development will reach 43.9 billion dollars by 2025 (https://dataforest.ai/blog/overview-of-the-natural-language-processing). The use of ChatGPT for all sorts of purposes is a good example of the growing influence of NLP and the role NLP will play in economic development in every industrial sector. 

Surely, it is not surprising. It is the human tendency to feel comfortable when we do things in a natural setting without resorting to being formal or having to unnecessarily adopt or modify our behaviors for a particular situation. Further, in hindsight, humans like to be in their comfort zone. So, anything that can facilitate our comfort has a high likelihood of being accepted and used. As such, NLP driven applications such as Siri, Alexa, and ChatGPT are very popular.

Just like other business domains, project management is expected to benefit hugely from the use of artificial intelligence and its various sub-sets, including NLP. One of the key challenges in the management of projects is dealing with a variety of stakeholders. Every time a new project is started, the project team has to deal with people that they may have never met or worked with before. So, managing stakeholders with all kinds of expectations, behaviors, and cultural contexts could be overwhelming. The use of technologies such as AI can be very useful in understanding the expectations of stakeholders and working with them effectively, thus enhancing the chances of project success.

In particular, the sentiment analysis of the stakeholder’s communication data (e.g., text) presents a significant opportunity to use NLP-driven solutions for improved project management. Sentiment analysis is defined as “the process of obtaining meaningful information and semantics from text using natural processing techniques and determining the writer’s attitude, which might be positive, negative, or neutral” (Nandwani & Verma, 2021, p. 2). While every type of project captures and retains data about communication with stakeholders, medium- to large-sized projects in particular are prone to capturing such data more actively. The data thus captured can be vital for analytics. Organizations deploying medium- to large-sized projects are more likely to have the resources to use the latest technologies, and hence they can benefit from the use of sentiment analysis.

Then the question is: how can sentiment analysis help with stakeholder management in projects? To answer that, below we present some potential uses of sentiment analysis for project stakeholder management. Needless to say, the ideas are neither conclusive nor exhaustive and are only meant to present some thoughts on the subject. 

The potential uses of sentiment analysis for project stakeholder management

  1. Proactive way of addressing concerns

The use of sentiment analysis provides any opportunity to analyze the data (e.g., coming via emails, text, or notes taken at meetings) to understand the feelings and emotions of stakeholders and address any concerns. The proactive monitoring of such data allows the project team to see red flags and check out any potential concerns. It gives the team an opportunity to firefight and meet stakeholders’ expectations.

Potentially, the team can organize a meeting with the relevant stakeholders to gain more knowledge and address their concerns as needed. In medium- and large-sized projects, the number of stakeholders can be quite large, and hence using sentiment analysis will help in proactive monitoring and addressing the issues.

  1. Effective handling of social media driven feedback

The use of social media has become part of day-to-day life and has brought about a paradigm shift in the dissemination of information. Not surprisingly, project-related information is also shared on social media. As projects involve both internal and external stakeholders, it provides opportunities for people to share their concerns and sentiments about the projects and their effects on the stakeholders.

The project team thus has the opportunity to harness social media-driven information, such as comments from stakeholders, to analyze and understand any potential concerns that require addressing. Since social media is accessible to everyone, not paying heed to information published on social media can be counterproductive and could result in projects facing scrutiny and delays.

However, one of the recent studies (e.g., Chung et al., 2023) suggests that more needs to be done to use social media content for stakeholder engagement and management. This finding partially indicates that the use of sentiment analysis for project stakeholder management is still in its infancy, and project organizations need to consider seizing the technological advancements in NLP for effective project management.

  1. Efficient crises management

Another area where sentiment analysis can help project teams is understanding the reactions and concerns of stakeholders in the event of a crisis. The sentiment analytics can help provide real-time insights about stakeholders’ concerns about the effects of crises. It will help project teams devise response strategies. The feedback about the benefits or drawbacks of response strategies can also be sentimentally analyzed for further improvements in stakeholder management.

Concluding thoughts: 

The wide-spread uptake of ChatGPT has illuminated the benefits of using NLP for business and day-to-day life purposes. Project management can certainly benefit from the use of NLP-based solutions. Project management is a soft skills-oriented approach requiring efficient handling of people. Anything that can help and support handling the human side of things is important. Hence, in hindsight, leveraging sentiment analysis for stakeholder management seems logical and natural.

However, the current body of knowledge (e.g., Chung et al., 2023; Prebanić & Vukomanović, 2022) highlights the need for furthering work and enhancing the uptake of sentiment analysis and other tools for effective project delivery. With that in mind, we have discussed a few areas of potential use of sentiment analysis for project stakeholder management. The intent is to emphasize the utility of the tool and generate some discussion around its potential utility and integration in day-to-day project work. Certainly, this is a limited note on the subject, and accessing related literature on the subject can add to gaining further insights.

References

Chung, K. S. K., Eskerod, P., Jepsen, A. L., & Zhang, J. (2023). Response strategies for community stakeholder engagement on social media: A case study of a large infrastructure project. International Journal of Project Management, 41(5), 102495.

Nandwani, P., & Verma, R. (2021). A review on sentiment analysis and emotion detection from text. Social network analysis and mining, 11(1), 81.

Prebanić, K. R., & Vukomanović, M. (2022). Exploring social media as mean to manage construction project stakeholders. In 15th International OTMC Conference and 6th IPMA Senet Conference: Smart Built Environment through Digital Transformation (pp. 23-39).

© 2024 Jiwat Ram, All Rights Reserved.

Written by
Jiwat Ram

Jiwat is a Professor in Project Management. He has considerable experience of working internationally in diverse cultures and business environments.

He has a growing portfolio of work on issues related to artificial intelligence, machine learning and large language models (LLMs). His work has been published in top scientific journals.

Jiwat actively contributes to project management community. More recently, he has published a number of articles on some of the contemporary issues confronting project management and business management in various industry based outlets.

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