Last month, I looked at Sentiment Analysis: Opportunities and Challenges, promising a follow-on focus on applications. It's the breadth of opportunities – promising ways text analytics can be applied to extract and analyze attitudinal information from sources as varied as articles, blog postings, e-mail, call-center notes and survey responses – and the difficulty of the technical challenges that make existing and emerging applications so interesting.
We will explore three applications – influence networks, assessment of marketing response and customer experience management/enterprise feedback management – via mini-case studies.
Influence Networks
Aafia Chaudhry, a physician who calls herself “a passionate enthusiast in the science of opinion leadership in healthcare systems,” is president of 81qd, a New York company that consults on pharmaceutical life-cycle management. Chaudhry applies text-analytics software from Linguamatics to perform targeted influence-mapping studies. She seeks to understand the correlation of physician sentiment, mined from sources that include event and interview transcripts, presentations, media releases and PubMed biomedical literature abstracts, with her clients' scientific and promotional messaging about therapies. She has purposely concentrated on sources where large volumes of readily mineable information are available; she is exploring adding blogs to the mix. 数据挖掘研究院
Jeff Catlin, CEO of text-analytics vendor Lexalytics, describes similar work at Cisco, which he characterizes as his company’s best success story. Cisco “used the sentiment engine to determine which executives have the highest correlation to positively moving the stock price when they deliver positive news. They found that certain executives had a positive influence on the markets, while others actually had a negative influence because of the tone of their delivery.”
Aafia Chaudhry's 81qd clients are “looking to develop relationships with key opinion leaders,” and text-mining along with peer-to-peer network analysis facilitate the task. She has been able to apply I2E Interactive Information Extraction software from Linguamatics to the text-mining task without modifications or extensions, although Phil Hastings, Linguamatics' business development director, notes that specialized thesauri could be brought in to handle sentiment extraction from sources whose language is less formal, containing colloquialisms and slang, than that used by physicians and biomedical researchers.
