Behavioral Mapping by Using NLP to Predict Individual Behaviors
| dc.contributor.advisor | H. Far, Behrouz | |
| dc.contributor.author | Jafari, Reyhaneh | |
| dc.contributor.committeemember | Behjat, Laleh | |
| dc.contributor.committeemember | Moussavi, Mahmood | |
| dc.date | 2023-02 | |
| dc.date.accessioned | 2022-11-17T16:37:43Z | |
| dc.date.available | 2022-11-17T16:37:43Z | |
| dc.date.issued | 2022-11-16 | |
| dc.description.abstract | "What candidates or team members will do in specific circumstances" has always been an important piece of information for most employees or team leaders to consider when making a decision. It takes a significant amount of time to determine who is the best candidate for a particular job position. Companies are looking for the most efficient method for making this decision. Most of the time, personality assessments are used to identify an individual’s character traits. Regardless of personality type, individuals will behave differently in a positive atmosphere than in a stressful one. Hence, characteristics alone can not predict behavior. Thus, text analysis and the identification of candidate behaviors (behaviorism) now enable companies to understand how people think, feel, and act in a given situation and then choose from a vast pool of candidates the best candidate for the job. By leveraging the existing intellectual property data associated with the behavioral mapping in AccuMatch Behavior Intelligence as well as expert data and using tools such as Amazon Comprehend Service (ACS), IBM Watson Natural Language Understanding (NLU), and Machine Learning (ML) techniques, various methods have been developed and analyzed in order to predict how individuals in a team become motivated, what their individual decision reference is, and what their execution style is. Therefore, this dissertation presents multiple proposed methods to predict Towards/Away, Internal/External, and Option/Procedure behavior and discusses the rationale behind the selection of these methods along with the results obtained. | en_US |
| dc.identifier.citation | Jafari, R. (2022). Behavioral mapping by using NLP to predict individual behaviors (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. | en_US |
| dc.identifier.uri | http://hdl.handle.net/1880/115505 | |
| dc.identifier.uri | https://dx.doi.org/10.11575/PRISM/40472 | |
| dc.language.iso | eng | en_US |
| dc.publisher.faculty | Schulich School of Engineering | en_US |
| dc.publisher.institution | University of Calgary | en |
| dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | en_US |
| dc.subject | Behavioural mapping | en_US |
| dc.subject | Sentiment analysis | en_US |
| dc.subject | Emotional analysis | en_US |
| dc.subject | NLU | en_US |
| dc.subject | NLP | en_US |
| dc.subject.classification | Engineering--Electronics and Electrical | en_US |
| dc.title | Behavioral Mapping by Using NLP to Predict Individual Behaviors | en_US |
| dc.type | master thesis | en_US |
| thesis.degree.discipline | Engineering – Electrical & Computer | en_US |
| thesis.degree.grantor | University of Calgary | en_US |
| thesis.degree.name | Master of Science (MSc) | en_US |
| ucalgary.item.requestcopy | true | en_US |