Importance of Sentiment Mapping through Social Media Analysis: The Right Approach to CI Conferences

Nov 3, 2022 | Competitive Intelligence
Sayantani Sen
Sentiment_analysis

Importance of Sentiment Mapping through Social Media Analysis: The Right Approach to CI Conferences

Importance of Sentiment Mapping through Social Media Analysis: The Right Approach to CI Conferences 1024 555 deepak

Introduction: Understanding Pharma CI Conferences

Medical and scientific conferences are intersection points for industry dialogue and pharma company announcements. The interaction with KOLs makes such events important sources of primary and secondary competitive intelligence. Pharma companies participate in conference coverage by attending symposiums, oral, poster and booth sessions that gauge competitor positioning and messaging. They use these CI events to present their latest clinical trials and promote their products by setting up promotional booths. Marketing and sales professionals use these booths as a platform for interaction with HCPs and KOLs.

Importance of Conference Coverages

A good conference coverage helps pharma companies gain meaningful competitive and market insights through comprehensive pre-conference planning. Companies can also gather effective intelligence via networking, by tracking industry trends in CI, innovations in medicine, discoveries, and advancements in drug availability. Most insight teams can glean intelligence from post-conference reports thereby enabling a critical understanding of presented data.

  • Medical conference also promotes pharma stakeholders to indulge in peer networking and help attend important Q&A events which are golden spots for interaction with a variety of people from the life sciences field
  • Life sciences professionals also can explore exciting new offerings in the field and attend to collaboration requests
  • New data and products in the pharma analytics business showcased to all participants in the event
  • Companies also use the messaging and relevant social interpretations from these conference coverages

Participation in CI Conferences: Stepwise Coverage

To derive high-quality actionable insights for a better industry perspective, DZ follows a step-by-step approach while covering conferences:

  • Pre-conference planning involves the preparation of an excel based planner with the list of all the sessions covering details across multiple parameters, such as rank / priority as per client’s requirements, title, author, company, type of session (poster, industry symposia, plenary and others) and date / timings
  • During the conference, DZ team provides on-ground and virtual CI support to help clients and keep close track of competitors and their evolving strategies
  • Post-conference activities include insightful and holistic reporting of key takeaways and emerging themes. A detailed report is created in which a summary of all the sessions is compiled. This summary includes poster sessions of main aims, methods, and implications. These themes are custom created for key pharma stakeholders, and help pharma majors uncover competitive insights, market trends, social media buzz, thoughts from KOLs, and industry reactions. At DZ, our team of insight professionals create a detailed report of the conference that includes a summary of all sessions. This elaborate summary of poster sessions includes aim, methods, conclusions, and implications. It also includes analysis from the conference, such as details on booths and social media presence. Our team of experts collect booth materials from competitors to reveal rival product positioning and key messaging themes to better understand competitor tactics

Sentiment Mapping through Social Media Analysis in CI Conferences

While a conference is on, pharma companies use social media platforms to publicise their developments and milestones. Strategy teams meticulously map user sentiments in social media platforms like Twitter. Team scans all the media in the form of videos, presentations and manuscripts shared by pharma companies on their social platforms. Certain pharma companies use a variety of opinion-lexicon methods to analyze text sentiment after extracting Twitter data. Some of the more popular sentiment mapping methods include the Valence Aware Dictionary for Sentiment Reasoning (VADER) model where a normalized score or a compound score is computed to sum up a valence score of each word in the input text. One of the benefits of using VADER is that social media analysts can gauge the contribution of each word to the sentiment of the tweet. Many neutral tweets are because of the choice of thresholds used for the compound score. A narrower threshold for neutral sentiment would produce fewer neutral tweets and more of either negative or positive.

Challenges in Mapping Sentiment across social media during Conferences

  • One of the key challenges that social media strategy teams face is the difficulty in analyzing a high volume of social media data using traditional tools
  • Understanding the sentiments of social posts becomes difficult given the high variability and dated technology
  • Lack of a well-synthesized and analyzed output that gives a holistic view of the complete conference is also a major pain point

At DZ, we study comments on Twitter about upcoming drugs through a deep dive analysis of medical abstracts. We employ a robust methodology to study the voice and engagement of each of these abstracts presented in social media platforms such as Twitter. This is a step-by-step approach that is critical in mapping user sentiment comprehensively. This enables us to deploy social media analysis across all channels to extract relevant data, remove noise, and identify insights.

Two-step approach is critical in mapping sentiments:

Once sentiment is mapped and analysts analyze the medical abstracts, there is an evaluation of the share of voice and engagement for each abstract. This abstract analysis is critical based on the number of mentions, reposts, likes, engagement and average engagement rate, the theme of posts, sentiments, the share of voices, and distribution of posts by users such as HCPs and patient advocates. Most pharma companies follow a step-by-step approach for shortlisting social media channels. They extract relevant data and remove noise to identify insights.

Parameter Check of High-Volume Twitter Posts

At DZ, we have a diverse team of programmers, social media experts, and pharma analysts to analyze this high-volume social media data.

  • We identify the top medical abstracts commented upon by users across Twitter
  • Analysis of these abstracts, the overall tweets distribution by theme and understanding whether the sentiment was positive on various parameters is critical
    • The parameters used to gauge sentiment include keywords such as new standard of care, breakthrough data, practice changing results, prolonged survival, first line choice, game changer, eye on toxicities and diversified clinical studies
    • Analysis was done to gauge whether the sentiment was positive across various parameters. These parameters include new standard of care, breakthrough data, practice changing results, prolonged survival, first line choice, game changer, eye on toxicities and diversified clinical studies.
  • Lack of a well-synthesized and analyzed output that gives a holistic view of the complete conference is also a major pain point
Executive_summary

Advantages of Mapping Sentiments in social media: Understanding Twitter

Opinion mining on Twitter specifically enables pharma marketers to socially listen to consumer health clients and understand their perspectives about drug lifecycles, usage, and availability in the overall market. Pharma majors can gain actionable insights in real-time for effective commercial decisions and compliance to safety norms at various stages of drug development. From drug development to drug launch and beyond, social media monitoring can provide drug makers with credible and influential information. Opinion mining helps healthcare providers with important information on drug research and release.

  • While analyzing these opinions via Tweets, social media analysts can check key discussion points like efficacy and drug safety of various oncology drugs for instance
  • Drug marketers are also able to derive key insights like KOL-led discussions, advice, opinions, and patient stories that can have a great impact on the target audience. Sample tweets can also be assessed to understand HCP concerns like the toxicity profiles of drugs

Sentiment Mapping with Advanced Analytics at DataZymes: The Final Word

At DataZymes, we utilize a blend of a modern advanced analytics platform that uses the best deep industry knowledge with human ingenuity to conduct in-depth social listening for the life sciences industry. An AI-powered patient intelligence tool is used with human ingenuity to conduct in-depth social listening for the life sciences industry to generate actionable insights. Our team of social media strategists identify influential physicians, KOLs and patient advocates to understand their perspectives about new emerging products to engage effectively with all pharma stakeholders. With sentiment mapping, we help pharma companies gain meaningful competitive and market insights through comprehensive pre-conference planning, effective information gathering during conference and gleaning of those from post-conference reports. Social media data, particularly from Twitter, helps companies map competitive intelligence and competitor performance. The volume of tweets can reveal significant insights about drugs in clinical trials or even in the discovery phase, for instance. Researchers, business analysts, and practitioners can adopt this kind of analysis to achieve their objectives and implement practical procedures for data collection, spam elimination, machine learning classification, feature categorization, and result visualization to name a few. Large amounts of social data can easily be analyzed using third-party tools utilizing Twitter API. Twitter API has a broader intended function and can assist CI professionals in pharma companies to help them monitor and benchmark a competitor’s social media efforts. These tools are flexible, low cost and relatively easy to use when extracting information from Twitter. With the use of Twitter API and its associated rich ecosystem of Python wrappers and libraries, social analysts can write automated programs that can run complex queries against Twitter data. This extracted data then using such techniques like frequency and simple statistical analysis can be used to develop understanding and intelligence to compete in the market and develop information for conference coverages.

References

Sunmoo Yoon, Noemie Elhadad, Suzanne Bakken. A Practical Approach for Content Mining of Tweets.
A Practical Approach for Content Mining of Tweets – PMC (nih.gov). National Library of Medicine.
July 1, 2014
 

Stephanie Stephens. Medical Conferences: Should I Stay, or Should I Go?
Medical Conferences: ‘Should I Stay or Should I Go?’ – healthecareers.com.
February 19, 2019
 

Safegraph. The Ultimate Guide to Competitive Intelligence Research.
The Ultimate Guide to Competitive Intelligence Research | SafeGraph.
2022
 

Arjan Singh. Collecting Competitive Intelligence at Conferences.
Collecting Competitive Intelligence At Conferences (lifescienceleader.com).
November 1, 2019.
 

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