Changes in Classwide Conduct: Leveraging Machine Learning to Overcome Challenges With Sentiment Analysis
Recording of a 90-minute CLE video webinar with Q&A
This CLE webinar will assist class action lawyers and other litigators in understanding sentiment analysis, its value in litigation, and how the latest advances in machine learning and AI can overcome challenges presented by more traditional analytical approaches. The program will discuss what sentiment or emotional analysis is and how it works, the various approaches used to obtain this data, the categories of cases in which it may be the most useful, and evidentiary challenges, as well as share success stories.
Outline
- Overview of sentiment analysis and its uses in litigation
- Sentiment analysis approaches
- Applying machine learning or other AI to conduct sentiment analysis
- Evidentiary issues
Benefits
The panel will discuss these and other key issues:
- What are the various approaches or forms of sentiment analysis?
- How can machine learning overcome some of the challenges to various forms of sentiment analysis?
- What are the evidentiary challenges to sentiment analysis derived from machine learning?
Faculty
Mike DeCesaris
Vice President, Data Science Center
Cornerstone Research
Mr. DeCesaris leads the Data Science Center at Cornerstone Research and coheads the firm’s technology, digital... | Read More
Mr. DeCesaris leads the Data Science Center at Cornerstone Research and coheads the firm’s technology, digital economy, and artificial intelligence practice. He plays a leading role in Cornerstone Research’s initiatives related to artificial intelligence (AI), generative AI (GenAI), and Large Language Models (LLMs). Mr. DeCesaris has more than twenty-five years of experience consulting on all phases of commercial litigation, internal investigations, and regulatory matters. He focuses on complex, data-intensive empirical projects at the intersection of economics, law, technology, and data science. Mr. DeCesaris works with counsel to efficiently manage the production and analysis of large, proprietary databases. His expertise includes issues related to healthcare, pharmaceuticals, the False Claims Act, antitrust and competition, merger reviews, intellectual property (IP), and allegations of consumer fraud, product misrepresentation, and breach of contracts. Mr. DeCesaris works on matters in numerous industries, notably airlines, consumer products, energy and commodities, financial services, healthcare, life sciences, technology, and telecommunications and media.
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Ernest Kim Song
Director, Data Science Center
Cornerstone Research
Mr. Kim Song has over ten years of experience consulting on all phases of commercial litigation, internal... | Read More
Mr. Kim Song has over ten years of experience consulting on all phases of commercial litigation, internal investigations, and regulatory matters. As director of Cornerstone Research’s Data Science Center, Mr. Kim Song leads interdisciplinary data scientists in applying artificial intelligence (AI), social media analysis, geospatial analysis, big data analytics, and machine learning (ML) techniques to support expert testimony. He consults on issues at the intersection of law, technology, big data, and data science. In these contexts, he has analyzed algorithmic trading platform code, interfaced with cryptocurrency network infrastructures, and conducted text analyses of information disseminated through social media and other communications platforms. Mr. Kim Song plays a leading role in Cornerstone Research’s initiatives to incorporate AI and Large Language Model (LLM) capabilities into litigation support.
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Kiriaki Tourikis
Attorney
Reed Smith
Ms. Tourikis is an associate in the Tech & Data group, focusing her practice on enterprise data risk management and... | Read More
Ms. Tourikis is an associate in the Tech & Data group, focusing her practice on enterprise data risk management and information governance, data privacy, records and e-discovery. She advises large financial services institutions on enterprise data risk management strategies to manage legal and regulatory issues associated with both traditional and innovative techonologies and data sources.Ms. Tourikis' practice involves advising clients on lowering risk associated with using and storing information across jurisdictions. In her role, she counsels large financial institutions, on all aspects of data risk management and the discovery and management of electronic data, including: data migrations; technology implementation and management; the policies and procedures regarding the governance of information in various technologies; eDiscovery strategy and management; the use of data analytics for eDiscovery, compliance and risk management; the development of data source catalogues, disclosures, and responses relating to electronically stored information; and the remediation of legacy data (both paper and electronic).
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