- Confidential Oil & Gas Co.
- Data collection using field surveys,
- Response translation,
- Data analysis using statistical measures,
- Developing action plans.
Tessellations has leveraged natural language processing and machine learning techniques to help an oil and gas client better understand stakeholder comments collected as a part of a socio-economic survey conducted on the project site. The data was captured in the field in Portuguese and available for stakeholder engagement analysis within 48 hours of collection.
Stakeholder perceptions are typically captured using either quantitative responses to closed ended questions or qualitative responses to open ended questions. The best insights come from very open ended questions such as “how do you feel about the project?” Making consistent sense out of open ended text comments has historically been both difficult and subjective.
Scope of Services
- Collecting field survey questions
- Translate responses from Portuguese to English
- Use conventional statistical methods to summarize the data
- Leverage natural language processing and machine learning to uncover hidden insights
- Developing action plans to manage and shape perceptions
- With this exercise Tessellations summarized the key stakeholder’s perceptions and expectations, how well they are being met, and how those are different based on affected groups. Using the same techniques over time would help track and monitor changes of the local residents’ perceptions of the project.