The Role of Sentiment Analysis in Risk Management

Sentiment analysis in risk management NLP's
January 13, 2022


Sentiment analysis can be used in security assessments and risk management to forecast risks and mitigate the exploitation of organizations’ online and physical vulnerabilities, before real-life damages occur.

Sentiment analysis refers to the use of natural language processing (NLP), computational linguistics, and text analysis to ascertain the attitudes or “feelings” of authors behind written text, or behind the written text itself. Through the use of algorithms to differentiate between the emotions typically associated with keywords, this technology can offer insights as to whether written communications suggest positive, negative, or neutral sentiment.

  • With the advent of social media and its widespread use, the world now finds itself with accessibility to a seemingly infinite amount of data, some of which was once considered private and intimate.
  • Using sentiment analysis tools, these data can render invaluable insights for industries to seek solutions for problems that address risk management, reputation management, and threat monitoring.

The color coding is an example representation of an intelligence tool’s sentiment analysis scheme, in which green may be representative of positive sentiment, grey may be representative of neutral sentiment, and red may be representative of negative sentiment.


Managing Online Risks

Sentiment analysis conducted on massive quantities of social media data can impart invaluable risk management insights about the proportions of online discussion dedicated to negative, hostile, or concerning rhetoric about target organizations or executives. Sentiment analysis can help industry manage risk and empower strategic and long-term decision making. This may encompass managing risks from unstable geographic regions, associations with high-profile entities, or new industries and markets.

  • Organizations with any online social media presence may confront challenges intersecting operations, business ethics, and corporate social responsibility. These risks might arise from aggrieved customers, advocacy groups, or even company insiders.
  • Some of this risk, however, can be mitigated using modern-day data mining and sentiment analysis tools. Classifications between positive, neutral, and negative sentiment on social media posts, forums, and blogs can help sort and make sense out of structured and unstructured data.
  • This analysis can then be used to inform organizations about their existing online risks, public perceptions, vulnerabilities, and how to adjust security postures to adequately address them.


Understanding Public Perceptions

Sentiment analysis also makes it possible to capture the real-time and historical sentiment trends of online users towards not just your organization, but your executives. Reputation management can be defined as monitoring -and sometimes influencing- how the public perceives your business, its activities, and its people. In some cases, it may also entail protecting or improving the reputation of an organization impacted by economic, political, or social factors.

  • With companies increasingly utilizing customer generated content on business review or social media sites, sentiment analysis has become a powerful technique to evaluate the impact of positive, neutral, or negative public perception on an organization or its high-level executives.
  • This information allows organizations to better understand and adjust cyber and physical security postures based on subtle changes in public perceptions of their brand, business dealings, associations, and the reputation that comes with them.


Monitoring Threats

Negative public perception of an organization or its people can also result in the manifestation of hostile or concerning narratives, or even real-life threats. Whether attempting to prevent incidents like the attack on the Capitol on 6 January 2021, or types of harassment or cyberstalking, sentiment analysis can help parse out concerning online chatter from a sea of “noise” before real-life physical violence occurs.

  • According to studies conducted by the Ontic Center for Protective Intelligence, in the previous 18 years, American male CEOs are a primary target for attackers. The study further found that while financial and tech industry executives were targeted the most, 40 percent of all individuals who experienced attacks were injured or killed as a result.
  • With roughly one-third of executives lacking executive protection teams, sentiment analysis has the ability to help identify, monitor, and report credible threats before virtual threats become real.


Staying A Step Ahead

With sentiment analysis-enabled business intelligence and analytics tools, it is now possible to actively track ill-intentioned online entities and their activities to prevent real-life violence or damages from occurring. With yearly rises in internet accessibility around the world, and the number of social media platforms -Twitter, Facebook, Instagram, and others-, and individual account holders, data has become a valuable currency. Similarly, the appetite for this data in risk management, reputation management, and threat monitoring has only grown, and sentiment analysis has proven to be one of the most powerful ways to make use of this data.


Author: José Gomez-Angúlo, Intelligence Associate for Concentric



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