Board path
Listening > Aggregated overview > Overview
Why use this board
Use this board for a consolidated view of listening performance across your queries; scan volume, sentiment, and topic signals in one place.
Board controls
-
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.
-
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.
-
Date range: Defaults to the last 30 days. The board subtitle shows the active range when available.
-
Aggregated by: Day, Week, Month, Quarter, Year.
-
Export: Export the table to XLSX, including the selected date range when available.
Metrics on this board
-
Number of authors — Authors by gender
-
Mentions — Topics
-
Potential impressions — Number of potential impressions
-
Social interactions — Number of social interactions
-
Number of mentions — Number of mentions
-
Mentions — Top themes
-
Mentions — Top positive keywords
-
Number of mentions — Sentiment of mentions trend
-
Number of authors — Authors trend
-
Number of mentions — Mentions trend
-
Mentions — Top languages
-
Authors — Top languages
-
Interactions — Top languages
-
Potential impressions — Top languages
-
Mentions — Top keywords
-
Mentions — Top emojis
-
Mentions — Top negative keywords
-
Authors — Top professions by X authors
-
Authors — Number of authors
-
Followers — Top authors by potential impressions
-
Potential Impressions — Top authors by potential impressions
-
Mentions — Top authors by potential impressions
-
Interactions — Top authors by potential impressions
-
Followers — Top authors by mentions
-
Mentions — Top authors by mentions
-
Interactions — Top authors by mentions
-
Potential Impressions — Top authors by mentions
-
Number of authors — Authors by age and gender
-
Mentions — Top countries
-
Authors — Top countries
-
Interactions — Top countries
-
Potential impressions — Top countries
-
Number of mentions — Sentiment of mentions by platform
-
Mentions — Top hashtags
-
Authors — Top hashtags
-
Interactions — Top hashtags
-
Potential Impressions — Top hashtags
-
Mentions — Top interests
-
Authors — Top interests
-
Interactions — Top interests
-
Potential Impressions — Top interests
-
Number of mentions — Mentions by platform
Widgets
Authors by gender
What it measures: The distribution of the total number of unique authors that produced mentions matching your analyzed queries, segregated by the author's gender. 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
Topics
What it measures: This table summarizes all detected topics among mentions matching the analyzed queries, as well as the sentiment and contextual words most frequently associated with them
Metrics: Mentions
Visualization: Table
Number of potential impressions
What it measures: The number of unique users who may see mentions matching the analyzed queries. Shown as a KPI with period-over-period change — use it to see whether the metric is rising or falling.
Metrics: Potential impressions
Visualization: Value with change
Number of social interactions
What it measures: The total number of user interactions received by mentions matching the analyzed queries. Shown as a KPI with period-over-period change — use it to see whether the metric is rising or falling.
Metrics: Social interactions
Visualization: Value with change
Number of mentions
What it measures: The number of content pieces matching the analyzed queries. Mentions discovered by multiple analyzed queries are counted only once. Shown as a KPI with period-over-period change — use it to see whether the metric is rising or falling.
Metrics: Number of mentions
Visualization: Value with change
Top themes
What it measures: Themes are specific topics detected in mentions matching the analyzed queries. You can think of themes as detailed points that can be grouped under interests. Each mention can have multiple themes. This metric shows the themes most frequently detected by our machine learning system, which can predict up to 10,000 different themes from mentions text. It supports English, Spanish, Portuguese, and partially Czech. 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: Mentions
Visualization: Word cloud
Top positive keywords
What it measures: An overview of the most frequently featured keywords with a Positive sentiment among mentions matching the analyzed queries. 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: Mentions
Visualization: Word cloud
Sentiment of mentions trend
What it measures: An overview of the total number of mentions matching the analyzed queries, segregated by sentiment (Positive, Negative, Neutral) and content publication date. Mentions discovered by multiple analyzed queries are counted only once.. Shown as a trend over time — use it to spot spikes, drops, and seasonality across the selected period.
Metrics: Number of mentions
Visualization: Line chart
Authors trend
What it measures: An overview of the number of unique authors that produced mentions matching the analyzed queries, segregated by content publication date. Authors who produced multiple mentions are counted only once. Authors who cannot be identified due to API limitations (e.g. via Instagram hashtag search) are not counted. Shown as bars over time — use it to compare day-by-day or period-by-period volume and spot spikes.
Metrics: Number of authors
Visualization: Bar trend
Mentions trend
What it measures: An overview of the total number of content pieces matching the analyzed queries, segregated by content publication date. Mentions discovered by multiple analyzed queries are counted only once. Shown as bars over time — use it to compare day-by-day or period-by-period volume and spot spikes.
Metrics: Number of mentions
Visualization: Bar trend
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
Top keywords
What it measures: The most frequently used keywords among mentions matching the analyzed queries, visualized in a word cloud. The more frequently a keyword appears in mentions, the larger its frame in the word cloud.
Metrics: Mentions
Visualization: Word cloud
Top emojis
What it measures: An overview of the most frequently featured emojis among mentions matching the analyzed queries. 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: Mentions
Visualization: Word cloud
Top negative keywords
What it measures: An overview of the most frequently featured keywords with a Negative sentiment among mentions matching the analyzed queries. 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: Mentions
Visualization: Word cloud
Top professions by X authors
What it measures: The most common professions among authors who generated X mentions matching the analyzed queries. Professions are derived from public X data, using job titles detected in account bios. Emplifi Listening supports 160 job title groups for accurate categorization. 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: Authors
Visualization: Word cloud
Number of authors
What it measures: The number of unique authors that produced mentions matching the analyzed queries. Authors who produced multiple mentions are counted only once. Authors who cannot be identified due to API limitations (e.g. via Instagram hashtag search) are not counted. Shown as a KPI with period-over-period change — use it to see whether the metric is rising or falling.
Metrics: Authors
Visualization: Value with change
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 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
Authors by age and 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 age and gender. 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
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
Sentiment of mentions by platform
What it measures: The distribution of sentiment (Positive, Negative, Neutral) for mentions matching the analyzed queries, segregated by platform (e.g. social media network, blog, forum, news site, etc.). Mentions discovered by multiple analyzed queries are counted only once. 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 mentions
Visualization: Stacked bar chart
Top hashtags
What it measures: The most frequently used hashtags across mentions matching the analyzed queries. 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
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
Mentions by platform
What it measures: The distribution of the total number of content pieces matching the analyzed queries, segregated by platform (e.g. social media network, blog, forum, news site, etc.). Mentions discovered by multiple analyzed queries are counted only once. Shown as a breakdown by category — use it when share of the total matters more than exact values.
Metrics: Number of mentions
Visualization: Pie / breakdown