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Receptiviti UI Documentation

website·Indexed 33 days ago

https://ui.receptiviti.com/docs/

Documentation for the Receptiviti UI, a tool for analyzing and visualizing language data. It covers project creation, data preparation, and the use of various analysis tools including worksheets, dashboards, and specialized charts such as Language Style Matching (LSM), circumplex, radar, and lollipop charts to derive insights from text.

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What's inside Receptiviti

  1. Overview of Default General Data Table Transcript Template

    This template provides a high-level personality comparison using a Summary bar chart. It tracks prominent LIWC measures: Analytical Thinking, Clout, Authentic, and Emotional Tone. Note: This template is currently a work in progress.

  2. Overview of Default Transcript Template

    The Default Transcript Template is designed for transcript insights, focusing on speaker dynamics, cognitive load, and group profiles across several specialized dashboards.

    Dashboards & Included Worksheets:

    • Group Commitment: Language Style Matching (LSM) Heatmap
    • Group Drives and Values: Group/Speaker Drives and Schwartz Values (Radar Charts)
    • Group Collaboration: "I" and "We" words, Certainty, Tentative, Positive/Negative Emotion (Line Charts), Group Time Orientation (Bar Chart), Future Focus (Line Chart)
    • Group Curiosity and Openness: Group Curiosity/Openness, Curiosity, and Open To Change Words (Radar/Line Charts)
    • Group DISC Profile: Group and Speaker DISC Profiles (Radar/Bar Charts)

  3. Overview of Bar Charts for categorical data analysis

    Bar charts in Receptiviti are used to plot multiple measures across various categories. They are specifically designed for categorical data variables such as speaker_name, gender, office_location, age, and tenure. This visualization helps discern how different geographic, demographic, or organizational groups score across framework measures (e.g., Big 5 Personality measures).

  4. Overview of Receptiviti UI capabilities

    The Receptiviti UI is a tool for analyzing and visualizing language data. It allows users to generate charts and graphs to simplify data interpretation and tell stories from their data. Additionally, users can upload datasets through the interface to be scored and subsequently download the resulting scores in CSV format for external analysis or workflow integration.

  5. Overview of Default Survey Template

    The Default Survey Template is designed for survey insights and includes a set of specific worksheets and an 'Organizational Culture' dashboard.

    Worksheets:

    • Positive vs. Negative Emotion (Bar Chart)
    • Emotions Breakdown (Bar Chart)
    • Admiration, Joy, Anger, and Fear Topics (Topics by Emotion & Highlights)
    • Drives, Schwartz Values, and Psychological States (Radar Charts)

    Dashboard: Organizational Culture

    • Includes Radar Charts for Drives, Schwartz Values, and Psychological States.

  6. Understand Language Style Matching (LSM) analysis

    Language Style Matching (LSM) measures the magnitude of grammatical mirroring between two or more people in a conversation transcript by calculating the similarity in their use of function words.

    Unlike the Heatmap chart (which provides a static snapshot of mean LSM and variance), the LSM chart maps data to time segments, allowing users to analyze dynamic trends, such as convergence (reaching consensus) or widening gaps (alienation) over the course of a conversation.

    Requirement: The uploaded dataset must contain a datetime component to map LSM to time segments on the chart.

  7. Analyze data using the Scatterplot chart

    The Scatterplot chart is used to combine two measures on the X and Y axes for multiple categorical data points. It is primarily used to:

    1. Compare the average score of the mean of two measures.
    2. Identify correlations (positive, negative, or uncorrelated) between two measures.
    3. Identify outliers in a dataset.

    Common categorical variables used for filtering with this chart include gender, office, location, age, and tenure.

  8. Generate a Highlights worksheet from Emotions or Topics data

    The 'Export to Highlights' feature creates a separate worksheet that provides an overview of the specific language (text examples) used to populate an 'Emotions by Topic' or 'Topics by Emotion' worksheet. This allows users to see the actual sentences contributing to the data, the sentence count for each emotion, and filter which emotions are displayed using the 'Sentence Emotions' drop-down menu.

    If a subset of emotions or topics was already selected in the source worksheet, those same facets will be preserved in the exported Highlights worksheet.

    1. In a working project, go to the Worksheets tab.
    2. Create a new worksheet using the Create Worksheets icons.
    3. Select either Emotions by Topic or Topics by Emotion.
    4. Select a specific topic from the chosen taxonomy.
    5. Click the Export to Highlights button located to the right of the graph, under Save.
    6. Select the new preview window that appears in the left-hand UI section to view the highlights table.

  9. Understand Radar Chart requirements and use cases

    The Radar Chart compares three or more normed measures across multiple categories on radially arranged axes. It is ideal for categorical variables (e.g., speaker, gender, office location, age, tenure) or group profiles (e.g., executive team profiles using Big 5 or DISC Personality profiling).

    Critical Requirements:

    • Only normed scores are supported.
    • Datasets must have samples of 350+ words for categorical variables or overall data to meet the minimum requirement for normed scores.
    • Negative values are not allowed for this chart type.

  10. Visualize group alignment using the Heatmap chart

    The Heatmap chart visualizes the magnitude of Language Style Matching (LSM) between groups (typically three or more verbose speakers). It uses colored cells to represent magnitudes, providing an overview of rapport and alignment between individuals or groups, which helps identify misaligned individuals. It is suitable for comparing demographics such as departments, office locations, ages, tenures, or gender.

  11. Understand the Interpersonal Circumplex chart dimensions

    The Interpersonal Circumplex chart visualizes two primary dimensions of social cognition: agentic and communal leadership qualities.

    • Agentic: Speakers emphasize pursuing personal goals, exerting willpower, and prioritizing individual motivations or desires.
    • Communal: Speakers emphasize building and maintaining relationships, cooperating, and connecting with others to meet group goals.

    These two dimensions can operate independently or together to define a person's leadership style as conveyed in their text.

  12. Understand the DISC personality framework

    The DISC chart maps personality types and behavioral styles using a four-quadrant model based on two dimensions: Bold vs. Reserved and People-focused vs. Task-focused. The four styles are:

    • D (Dominant): Ambitious, active, bold leaders.
    • I (Influence/Inducement): Lead through connections, creativity, and collaboration.
    • S (Stable/Submissive/Steady/Supportive): Faithful, modest, methodical, and value relationships.
    • C (Compliant/Conscientious/Cautious): Prefer accuracy, unobtrusiveness, and impersonality.