Board path
Listening > Audience > Overview
Why use this board
Use this board to understand who is driving conversation for your queries; review audience composition signals that shape targeting and messaging.
Board controls
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Select data source: Select Listening Queries or Listening Query Sets. In order to use another data source type, please delete the current one and add a different data source type.
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Adaptive filters: Open Filter in the toolbar to narrow posts by Platform, Content Label, Sentiment, Language, Country, Interest, Media Type, Content Type, Full-text, or Advanced filter. Active filters appear as chips below the toolbar; remove a chip to clear that filter.
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Date range: Defaults to the last 30 days. The board subtitle shows the active range when available.
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Aggregated by: Day, Week, Month, Quarter, Year.
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Export: Export the table to XLSX, including the selected date range when available.
Metrics on this board
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Number of authors — X authors by age trend
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Mentions — Top countries
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Authors — Top countries
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Interactions — Top countries
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Potential impressions — Top countries
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Followers — Top authors by potential impressions
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Potential Impressions — Top authors by potential impressions
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Mentions — Top authors by potential impressions
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Interactions — Top authors by potential impressions
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X authors — Top professions by X authors
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Number of authors — X authors by age
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Followers — Top authors by mentions
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Mentions — Top authors by mentions
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Interactions — Top authors by mentions
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Potential Impressions — Top authors by mentions
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Mentions — Top interests
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Authors — Top interests
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Interactions — Top interests
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Potential Impressions — Top interests
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Mentions — Top languages
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Authors — Top languages
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Interactions — Top languages
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Potential impressions — Top languages
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Number of authors — X authors by gender trend
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Number of authors — X authors by gender
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Number of authors — X authors by age and gender
Widgets
X authors by age trend
What it measures: An overview of the distribution of unique authors who produced content matching the analyzed queries, segregated by the age of the author and the date of the mention's publication. This metric uses public X data. Age is derived from data detected in X authors' bios. Shown as a trend over time — use it to spot spikes, drops, and seasonality across the selected period.
Metrics: Number of authors
Visualization: Line chart
Top countries
What it measures: This table ranks countries based on where the majority of your mentions originate, determined by the location of the mention's author. For X, the country is defined by the geolocation of the author's device. If unavailable, it's assigned automatically by Emplifi's AI tool or manually by our research team. For Facebook and Instagram, geolocation is assigned automatically or manually by our team. Please note that while the country is assigned to many social media profiles, some may be omitted.
Metrics: Mentions, Authors, Interactions, Potential impressions
Visualization: Table
Top authors by potential impressions
What it measures: This table ranks authors by highest potential impressions. It highlights the authors of content matching the analyzed queries with the most significant reach and impact. For X, YouTube, Facebook, and Instagram, potential impressions are equal to the author's follower count at the time of the mention. Authors from Web sources (News, Blogs, and Forums) are listed only if there are fewer than 50 authors from other Listening sources. Due to API limitations, authors of mentions detected by Instagram hashtag search are listed as Unknown, with only one mention. Facebook personal profiles' impressions data are unavailable.
Metrics: Followers, Potential Impressions, Mentions, Interactions
Visualization: Table
Top professions by X authors
What it measures: The most frequently detected professions of X authors who produced tweets matching the analyzed queries. This metric uses public X data. Professions are derived from the job titles detected in X authors' bios. Our machine learning system supports 160 job title groups. Shown as a word cloud — larger labels mean higher frequency; use it to spot the most common themes, keywords, or hashtags in your data.
Metrics: X authors
Visualization: Word cloud
X authors by age
What it measures: The distribution of the number of unique authors who produced content matching the analyzed queries, segregated by the age of the author. This metric uses public X data. Age is derived from data detected in X authors' bios. Shown as vertical bars — compare categories side by side to see which drives the most volume.
Metrics: Number of authors
Visualization: Bar chart
Top authors by mentions
What it measures: This table ranks authors by the number of mentions they've produced that matched the analyzed queries. Authors who cannot be identified due to API limitations (e.g. via Instagram hashtag search) are displayed as Unknown profiles. Such profiles are listed with only one mention, since there's no way to aggregate the mentions to a unique author.
Metrics: Followers, Mentions, Interactions, Potential Impressions
Visualization: Table
Top interests
What it measures: This table ranks the most frequently detected interests among mentions matching the analyzed queries. Interests are broader than themes, representing general areas of discussion detected in mentions matching the analyzed queries. A single mention can contain multiple interests. This metric shows the interests most frequently detected by Emplifi's machine learning system, which can predict up to 320 different interests. It supports Arabic, Czech, German, English, Spanish, French, Indonesian, Korean, Portuguese, Russian.
Metrics: Mentions, Authors, Interactions, Potential Impressions
Visualization: Table
Top languages
What it measures: The most frequently used languages in mentions matching the analyzed queries, as detected by Emplifi's machine learning system. In some cases, the language detected by X can differ from Emplifi's and may display a different set of languages than expected. Shown in a sortable table — use it for exact values per row and to compare individual items (for example agents, profiles, or authors).
Metrics: Mentions, Authors, Interactions, Potential impressions
Visualization: Table
X authors by gender trend
What it measures: An overview of the distribution of unique authors that produced mentions matching your analyzed queries, segregated by the author's gender and the date of the mention's publication. This metric uses public X data. Gender is derived from data detected in X authors' bios. Shown as a trend over time — use it to spot spikes, drops, and seasonality across the selected period.
Metrics: Number of authors
Visualization: Line chart
X authors by gender
What it measures: The distribution of the total number of unique authors that produced mentions matching the analyzed queries, segregated by the author's gender. This metric uses public X data. Gender is derived from data detected in X authors' bios. Shown as a breakdown by category — use it when share of the total matters more than exact values.
Metrics: Number of authors
Visualization: Pie / breakdown
X authors by age and gender
What it measures: The distribution of the number of unique authors who produced content matching the analyzed queries, segregated by the age and gender of the author. This metric uses public X data. Age and gender are derived from data detected in X authors' bios. Shown as stacked bars — each segment shows a category's share of the total; use it to see composition, not just the headline number.
Metrics: Number of authors
Visualization: Stacked bar chart