Personality Detection and Analysis using Twitter Data

Personality types are important in various fields as they hold relevant information about the characteristics of a human being in an explainable format. They are often good predictors of a person's behaviors in a particular environment and have applications ranging from candidate selection to marketing and mental health. Recently automatic detection of personality traits from texts has gained significant attention in computational linguistics. Most personality detection and analysis methods have focused on small datasets making their experimental observations often limited. To bridge this gap, we focus on collecting and releasing the largest automatically curated dataset for the research community which has 152 million tweets and 56 thousand data points for the Myers-Briggs personality type (MBTI) prediction task. We perform a series of extensive qualitative and quantitative studies on our dataset to analyze the data patterns in a better way and infer conclusions. We show how our intriguing analysis results often follow natural intuition. We also perform a series of ablation studies to show how the baselines perform for our dataset.Comment: Submitted to ASONAM 202

Analysis and visualization of multimodal socio-technical information of free/libre and open source software (FLOSS) Projects

Personality traits influence most, if not all, of the human activities, from those as natural as the way people walk, talk, dress and write to those most complex as the way they interact with others. Most importantly, personality influences the way people make decisions including, in the case of developers, the criteria they consider when selecting a software project they want to participate. Most of the works that study the influence of social, technical and human factors in software development projects have been focused on the impact of communications in software quality. For instance, on identifying predictors to detect files that may contain bugs before releasing an enhanced version of a software product. Only a few of these works focus on the analysis of personality traits of developers with commit permissions (committers) in Free/Libre and Open-Source Software (FLOSS) projects and their relationship with the software artifacts they interact with. This thesis presents an approach, based on the automatic recognition of personality traits from e-mails sent by committers in FLOSS projects, to uncover relationships between the social and technical aspects that occur during software development processes. Experimental results suggest the existence of some relationships among personality traits projected by the committers through their e-mails and the social (communication) and technical activities they undertake.Maestrí

Psychological Understanding of Textual journals using Natural Language Processing approaches

Recent NLP advancements have improved the state-of-the-art in well-known datasets and are appealing more attention day by day. However, as the models become more complicated, the ability to provide interpretable and understandable results is becoming harder so the trade-off between accuracy and interpretability is a concern that is yet to be addressed. In this project, the aim is to utilize state-of-the-art NLP models to provide meaningful insight from psychological real-world documents that contain complex structures. The project involves two main chapters each including a different dataset. The first chapter is related to binary classification on a personality detection dataset, while the second one is about sentiment analysis and Topic Modeling of sleep-related reports

Constructing knowledge management capacity and forms of capital: a qualitative, ethnographic, exploratory case study of an Australian regional university education research team

This thesis explores the gap in knowledge pertaining to the research problem of how and why a specific group of knowledge workers individually and collectively constructed their knowledge management (KM) capacity. The knowledge workers studied were situated within the context of an academic research team working in the (then) education faculty of an Australian regional university between 25 January 2011 and 1 December 2012. The research problem led to the articulation of three research questions (RQs): (RQ1) What was the KM capacity profile of the research team and its members? (RQ2) How did the research team members construct their KM capacity? and (RQ3) What was the relationship between the team’s KM capacity and the team members’ economic, cultural and social forms of capital? An interdisciplinary literature review in Chapter 2 resulted in the definition of KM capacity used within this study, wholistically framed by four dimensions: process, human, technology and context. Each of these KM dimensions was composed of various subdimensions. Based on that literature review, a conceptual framework was developed in Chapter 3, adapted from a model published by Van Winkelen and McKenzie (2011), and extended to incorporate economic, cultural and social forms of capital as identified by Bourdieu (1986), presented as a KM capacity-capital architecture. The study’s research design was qualitatively orientated, was situated in the social constructivist paradigm, and deployed an exploratory, ethnographic case study approach as explained in Chapter 4. The data collection and analysis techniques to address each RQ were detailed in Chapter 5. The data analysis in response to RQ1 developed a qualitative KM capacity profile of each participant, describing who they were, as presented in Chapter 6. In response to RQ2, a thematic analysis of the semi-structured interview and focus group transcripts, and the ethnographic, observational evidence across all four of the KM capacity dimensions, detailed how the participants collaboratively co-constructed their KM capacity, as discussed in Chapter 7. For RQ3, Chapter 8 triangulated thematic analysis of all data sources to consider why the participants constructed their KM capacity in relation to forms of economic, cultural and social capital (Bourdieu, 1986). The RQs1, 2 and 3 findings supported and refined wholistic comprehension of the how and why of contemporary KM capacity. The theoretical contributions arose from the synthesis and support of the KM capacity-capital architecture to reveal the relationship between the construction of the four KM capacity dimensions and the forms of economic, cultural and social capital within the context of a contemporary, academic research team. The methodological contributions were related to the triangulated analysis of multiple data sources and the visualisation of the findings. The practice-related contributions stem from the relevance of the KM capacity-capital architecture to understanding the how and why of KM worker dynamics