AI Driven Keyword Extraction and Trend Analysis Workflow

Keyword Extraction and Trend Identification Process

1. Data Collection

1.1 Identify Sources

Determine the relevant audio or video sources for transcription, such as interviews, focus groups, or webinars.

1.2 Utilize AI Transcription Tools

Implement AI-driven transcription tools such as Otter.ai or Rev.ai to convert audio data into text format efficiently.

2. Data Preprocessing

2.1 Clean Transcribed Data

Review and edit the transcribed text for accuracy, removing any irrelevant content or errors.

2.2 Format Data for Analysis

Standardize the text format to ensure consistency, which may involve removing special characters and normalizing case.

3. Keyword Extraction

3.1 Implement Natural Language Processing (NLP)

Utilize NLP libraries such as spaCy or NLTK to identify keywords and phrases within the cleaned text.

3.2 Use AI-Driven Tools for Enhanced Extraction

Consider employing AI tools like MonkeyLearn or TextRazor to automate keyword extraction and improve accuracy.

4. Trend Identification

4.1 Analyze Keyword Frequency

Conduct frequency analysis on the extracted keywords to identify prominent themes and trends.

4.2 Visualize Trends

Utilize data visualization tools such as Tableau or Power BI to create visual representations of keyword trends over time.

5. Reporting and Insights

5.1 Generate Reports

Compile the findings into comprehensive reports that highlight key trends and insights derived from the analysis.

5.2 Share Findings with Stakeholders

Present the reports to relevant stakeholders, utilizing presentation tools like Google Slides or Microsoft PowerPoint to communicate the insights effectively.

6. Continuous Improvement

6.1 Gather Feedback

Collect feedback from stakeholders on the relevance and utility of the insights provided.

6.2 Refine Processes

Continuously improve the keyword extraction and trend identification process based on stakeholder feedback and emerging AI technologies.