Analyzing sentiment is more than just measuring metrics. You need a lot of data to understand what your users’ thoughts and opinions are. It gets even more difficult when analyzing social media, where messages are full of acronyms, misspellings, sarcasm, and images. Most out-of-the-box solutions like natural language processors only label data as “positive,” “negative,” or “neutral,” with any unclear data ending up in the “neutral” bin. How can you understand what your users are saying if your natural language processor is only about 70% accurate?
Sentiment analysis on CrowdFlower is successful where automated solutions are not. Our human contributors review the data and extract the intention or meaning based on context clues. Humor, sarcasm, irony, and slang are no problem. And unlike automated solutions, our contributors can extract data from images, graphics, and videos as well as simple text. You can then use this deeper, richer data to train your machine learning algorithms.
With the people-powered sentiment analysis of CrowdFlower, you will:
- Analyze more than just keywords or phrases – our contributors will help you uncover real, actionable insights.
- Identify trends or crises early so you can adapt and grow.
- Save time and money with the world’s largest 24/7 labor pool to clean and enrich your data.
CrowdFlower can help you move beyond just “positive” or “negative” metrics to really understand what your users are saying about your brand. Give us a try today!