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Gathering knowledge regarding personality traits has long been the interest of academics and researchers in the fields of psychology and in computer science. Analyzing profile data from personal social media accounts reduces data collection time, as this method does not require users to fill any questionnaires. A pure natural language processing (NLP) approach can give decent results, and its reliability can be improved by combining it with machine learning (as shown by previous studies).

In this, cleaning the dataset and extracting relevant potential features “as assessed by psychological experts” are essential, as Indonesians tend to mix formal words, non-formal words, slang and abbreviations when writing social media posts. For this article, raw data were derived from a predefined dominance, influence, stability and conscientious (DISC) quiz website, returning 316,967 tweets from 1,244 Twitter accounts “filtered to include only personal and Indonesian-language accounts”. Using a combination of NLP techniques and machine learning, the authors aim to develop a better approach and more robust model, especially for the Indonesian language.

The authors find that employing a SMOTETomek re-sampling technique and hyperparameter tuning boosts the model’s performance on formalized datasets by 57% (as measured through the F1-score).

The process of cleaning dataset and extracting relevant potential features assessed by psychological experts from it are essential because Indonesian people tend to mix formal words, non-formal words, slang words and abbreviations when writing tweets. Organic data derived from a predefined DISC quiz website resulting 1244 records of Twitter accounts and 316.967 tweets.

This study explores one-to-one LEGO® Serious Play® in positive psychology coaching (1-1 LSP in PPC) as an intervention to help emerging adults (EAs) in higher education develop a growth mindset.

This is a qualitative single-participant case study of an EA undergraduate student's experience with 1-1 LSP in PPC to help him navigate uncertainty about making a decision that he felt would influence his future career.

1-1 LSP in PPC enabled the participant to create a metaphoric representation of how a growth mindset operated for him, promoting self-awareness and reflectivity. The LEGO® model that the participant built during his final session acted as a reminder of the resources and processes he developed during coaching, which helped him navigate future challenges.

This study contributes to the emerging literature on the impact of using LSP as a tool in one-to-one coaching in higher education. The participant's experience demonstrates that 1-1 LSP in PPC may be an effective way to support positive EA development. More research is needed to explore its potential.

This study provides a possible roadmap to incorporate 1-1 LSP in PPC into coaching in higher education as a reflective tool to build a growth mindset in EA students.

Because most undergraduates are EAs navigating the transition from adolescence into adulthood, universities would benefit from adopting developmentally informed coaching practices. 1-1 LSP in PPC may be an effective intervention that provides the structured and psychologically safe environment EAs need to develop lasting personal resources.