Sentiment Analysis

A bank's communications team tracks sentiment around its own brand and the wider financial sector every month. Rather than relying on customer satisfaction surveys alone, they use media and social sentiment data to see how the bank is perceived by people who are not yet customers, by journalists, and by the wider public. When sector-wide negative sentiment rises, such as during a period of interest rate changes or regulatory news, the team can see whether the bank is being treated more or less favorably than competitors and prepare messaging accordingly.

A public relations agency needs to show clients not just how many times their brand was mentioned during a PR campaign, but whether the coverage generated was actually favorable. The monthly client report includes a sentiment breakdown showing positive, negative, and neutral coverage as a percentage and in volume, alongside comparison figures from previous months. This gives clients a more honest assessment of campaign results than mention counts alone and helps the agency demonstrate the actual value of earned media it has generated, not just its quantity.

A television channel wants to understand how audiences are reacting to its news coverage and programmes on social media, not just how many people are talking about them. The sentiment breakdown shows the channel's digital team whether audience reaction to a specific broadcast or on-air personality is broadly positive, critical, or polarized. This feeds into editorial and programming decisions and helps the management team understand whether audience engagement figures are driven by appreciation or by controversy, which have very different implications for the channel's brand and advertiser relationships.

A research organization studying how a specific topic, such as climate, gender, or economic inequality, is framed in Bangladeshi media needs structured sentiment data over a defined period to support its analysis. The team uses sentiment breakdowns by outlet type, publication date, and topic to identify how the framing of an issue has shifted over time and whether certain media types are consistently more positive or negative on the topic than others. This provides an empirical foundation for research conclusions that would otherwise rely on selective reading of coverage rather than a structured analysis of the full dataset.