Introducing CIPHER
Qualitative Data Utilizing the Power of AI
Computational Intelligence Platform for Humanistic Evaluation and Research (CIPHER) is an artificial intelligence tool designed to provide clients with a comprehensive assessment of their organization’s workplace based on employee feedback, collected from focus groups, interviews, and surveys; leveraging Artificial Intelligence (Natural Language Processing) and Machine Learning for analyses.
Capabilities include:
Identifying topics in an organization’s workplace policies
Identifying topics in employee responses
Analyzing sentiment in employee responses
Analyzing emotions in employee responses
Integrating information across topic, sentiment, and emotion analyses
Generating plots and visualizations for analysis reports
With our combined-capabilities approach, we can assess alignment between policies and employee responses from focus groups, interviews, and surveys, uncovering valuable insights.
Topic Modeling
CIPHER is able to identify topics across multiple documents and tracks how frequently each topic appears. If no topics are prespecified by an organization, we can implement exploratory approaches to find out what topics emerge naturally from the data.
The model determines frequency and similarity of words in order to identify patterns, which CIPHER groups into topics. The generated topics provide insights into the themes employees tend to discuss in interviews and/or focus groups, and serve as the foundation for sentiment and emotion analyses.
Sentiment Analysis
Qualitative data uploaded to CIPHER can also be analyzed to detect the overall sentiment of each sentence, in responses to specific questions, or across entire documents. The ability to take into account the context in which each word is used enables us to gain a more in-depth understanding of the underlying sentiment as being either positive, neutral, or negative. By analyzing sentence structure and context, CIPHER delivers a more accurate interpretation of the sentiment expressed by employees, in ways that simpler models can miss. This enables organizations to gauge the attitudes and general mood of employee responses to better understand how these relate to topics discussed in focus groups and interviews.
Emotion Analysis
By utilizing powerful context-aware algorithms, CIPHER can also detect a broad range of nuanced emotions relevant to organizations (examples include, but are not limited to, pride, enthusiasm, confidence, curiosity, uncertainty, frustration, fear, trust, hope and loyalty). These powerful pre-trained models for emotion analyses applied by CIPHER can be customized to meet specific client needs.
When combined with identified topics, emotion analyses enable the assessment of emotional tone behind each one. This ability to detect and analyze how emotions relate to topics that arise in interviews or focus groups can help organizations better understand how employees feel about their work, colleagues, or the workplace overall, in ways that inform effective management decisions.
By integrating these analyses with survey data on culture - related and/or other metrics of interest, we provide a comprehensive view of an organization’s workplace dynamics.
This combined approach allows us to relate qualitative insights with quantitative measures, uncovering deeper connections that inform strategic decisions that can strengthen organizational culture.