This American Life Podcast Transcript Dataset

This American Life Podcast Transcripts with Speaker Information and Timestamps

By Chris Jewell [source]

About this dataset

> This dataset provides a comprehensive collection of the transcripts for every episode of the popular podcast This American Life since its inception in November 1995. The dataset includes detailed speaker information, timestamps, and act or segment names for each line spoken throughout the episodes. > > With a focus on web scraping using Python and utilizing the powerful BeautifulSoup library, this dataset was meticulously created to offer researchers and enthusiasts an invaluable resource for various analytical purposes. Whether it be sentiment analysis, linguistic studies, or other forms of textual analysis, these transcripts provide a rich mine of data waiting to be explored. > > The informative columns in this dataset include episode number, radio date (when each episode was aired), title (of each episode), act name (or segment title within an episode), line text (the spoken text by speakers), and speaker class (categorizing speakers into different roles such as host, guest, narrator). The timestamp column further enhances the precision by indicating when each line was spoken during an episode. > > In summary, this comprehensive collection showcases years' worth of captivating storytelling and insightful discussions from This American Life

How to use the dataset

> > > - Exploring Episode Information: > - The episode_number column represents the number assigned to each episode of the podcast. You can use this column to identify and filter specific episodes based on their number. > - The title column contains the title of each episode. You can utilize it to search for episodes related to specific topics or themes. > - The radio_date column indicates when an episode was aired on the radio. It helps in understanding chronological order and exploring episodes released during specific time periods. > > - Analyzing Speaker Information: > - The speaker_class column classifies speakers into different categories such as host, guest, or narrator. You can analyze speakers based on their roles or categories throughout various episodes. > - By examining individual speakers' lines using the line_text column, you can explore patterns in speech or track conversations involving specific individuals. > > - Understanding Act/Segment Details: > - Some episodes may have multiple acts or segments that cover different stories within a single episode. The act_name column provides insight into these act titles or segment names. > > - Utilizing Timestamps: > - Each line spoken by a speaker is associated with a timestamp represented in the timestamp field.This enables mapping spoken lines with specific points within an episode. > > 5: Textual Analysis: > * Perform sentiment analysis by analyzing text-based sentiments expressed by different speakers across various episodes. > * Conduct topic modeling techniques like Latent Dirichlet Allocation (LDA) to identify recurring themes or topics discussed in This American Life episodes. > * Utilize natural language processing techniques to understand linguistic patterns, word frequencies, and sentiment changes over time or across different speakers. > > Please note: > - Ensure you have basic knowledge of data manipulation, analysis, and visualization techniques. > - Consider preprocessing the text data by cleaning punctuations, stopwords, and normalizing words for optimal analysis results. > - Feel free to combine this dataset with external sources like additional transcripts for comprehensive analysis. >

Research Ideas

> - Sentiment Analysis: With the transcript data and speaker information, this dataset can be used to perform sentiment analysis on each line spoken by different speakers in the podcast episodes. This can provide insights into the overall tone and sentiment of the podcast episodes. > - Speaker Analysis: By analyzing the speaker information and their respective lines, this dataset can be used to analyze patterns in terms of who speaks more or less frequently, which speakers are more prominent or influential in certain episodes or acts, and how different speakers contribute to the narrative structure of each episode. > - Topic Modeling: By using natural language processing techniques, this dataset can be used for topic modeling analysis to identify recurring themes or topics discussed in This American Life episodes. This can help uncover patterns or track how certain topics have evolved over time throughout the podcast's history

Acknowledgements

> If you use this dataset in your research, please credit the original authors. > Data Source > >

License

> > > License: Dataset copyright by authors > - You are free to: > - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. > - Adapt - remix, transform, and build upon the material for any purpose, even commercially. > - You must: > - Give appropriate credit - Provide a link to the license, and indicate if changes were made. > - ShareAlike - You must distribute your contributions under the same license as the original. > - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: episode_info_clean.csv

File: lines_clean.csv

Acknowledgements

> If you use this dataset in your research, please credit the original authors. > If you use this dataset in your research, please credit Chris Jewell.