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Sentiment Analysis Overview and State of the Art with TDM Studio

Sentiment Analysis Overview and State of the Art with TDM Studio Online

Sentiment Analysis or Sentiment Classification is valuable for answering lots of different research question: How does public sentiment react to different tragic events? Do tragic events always elicit the same negative emotional states? What publicly expressed emotions help politicians get elected? Have the most common emotions changed over the last 150 years? In this 1-hour workshop, we will use TDM Studio to learn about Sentiment Classification and also run two approaches to the task—One will be a baseline dictionary-based approach and the other a more recent SBERT-based model that performs at the state of the art for newspaper sentiment classification.

 

Related LibGuide: Text and Data Mining with TDM Studio by Sarah Young

Date:
Monday, December 4, 2023
Time:
10:00am - 11:00am
Time Zone:
Eastern Time - US & Canada (change)
Campus:
Virtual Workshop
Categories:
  Working With Data and Code  
Online:
This is a virtual event. A URL to participate will be sent via a reminder email 24 hours before the event.
Registration has closed.

Virtual Workshop Information:

  • The link to join this event will be found in your reminder email 24 hours before the event. 
  • Please join a few minutes early to ensure that your audio setup is working correctly.
  • All events are shown in Pittsburgh time. Visit this time zone converter to see when this event will take place in your time zone.

Workshops and events for Carnegie Mellon University Libraries are open to all, regardless of race, color, national origin, sex, disability, age, sexual orientation, gender identity, religion, creed, ancestry, belief, veteran status or genetic information. All participants are required to follow the Code of Conduct.

If you require accessibility accommodations, please contact the event organizer.

Organizer(s)

Profile photo of Emily Bongiovanni
Emily Bongiovanni
Profile photo of Sarah Young
Sarah Young