Linguistics-Data-Analysis

Data analysis for Linguistics Course research project regarding how people say goodbye (leave-takings).

Contents

• data.csv: 140 instances of leave-takings and their context that I collected from paying attention to how people indicate the end of a conversation.
• clean_data.csv: file generated in DataAnalysis.ipynb with the cleaned and transformed version of the original data
• DataAnalysis.ipynb: iPython Notebook containing steps of data cleaning and transformation, analysis, and visualization
  • Data transofrmation was done using pandas and numpy
  • Visualizations are made with matplotlib and use the seaborn-pastel style

Conclusions based on the data

• Familiarity between conversers has a huge impact on what kind of leave-taking is choosen. People tended to use a variety of "thanks" in professional settings while using something like “bye” or “see you later” much more often in unprofessional settings or when talking to friends or other familiar people. Based on this data, we can conclude that people shift into different styles based on their relationship with their interlocutor and their setting and this is demonstrated by how they end their conversations.
• Another interesting pattern came out when looking at age as the independent variable that leads to socio-linguistic variation. My data may indicate that young adults are leading the change away from “thanks” as a leave-taking or the pattern may simply indicate that people change which variable over their lifetime or based on the setting. Another of my initial hypotheses was that gender would play a role in leave-taking variation. This turned out to not be significantly supported by my data.