Track social listening trends with graph report

Use graph reports to track how social listening metrics change over time. Pull daily or monthly time-series data to visualize conversation trends, measure campaign momentum, and analyze brand mention patterns in BI tools like Power BI, Tableau, or Looker.

The Social Listening report provides aggregated metrics only. For full access to individual posts, top keywords, sentiment breakdowns, and web results, use the Social Listening API.

Use cases

Tracking conversation volume and engagement over time reveals campaign impact and identifies momentum shifts. Graph reports provide day-by-day or month-by-month breakdowns for trend analysis.

Campaign momentum tracking

Chart daily engagement and post volume during product launches to measure conversation growth

Brand health monitoring

Track engagement trends to identify when brand conversations gain or lose momentum

Competitive trend analysis

Compare monthly metrics against previous periods to benchmark performance

Executive reporting

Visualize social listening KPIs in Tableau or Power BI for stakeholder dashboards

Before you start

Make sure you have:

API Key: Your authentication token
Brand ID: The brand to track social listening data for

See our API Quickstart for help getting these.

Need to create a topic? See Monitor Brand Mentions with Social Listening API to set up your first topic.

Implementation

Step 1: Get your topic ID

Retrieve your topic ID to identify which conversation to analyze.

GET https://listening.dashsocial.com/organizations/{organization_id}/topics

Key query parameters

organization_id: Your organization’s unique ID

If you don’t have your organization ID, call GET https://auth.dashsocial.com/api/self using your API key:

curl 'https://auth.dashsocial.com/api/self' \
  -H 'Authorization: Bearer {token}'

Sample response:

{
    "accessible_brands": [144],
    "brands": {
        "your-brand": {
            "id": 144,
            "name": "Your Brand",
            "organization": {
                "id": 1,
                "name": "Your Organization"
            },
            "organization_id": 1
        }
    },
    "organization": {
        "id": 1,
        "name": "Your Organization"
    },
    "organization_id": 1
}

Look for organization_id at the top level of the response. Sample response:

{
    "data": [
        {
            "id": 11423,
            "name": "New cosmetic release 2025",
            "audience_type": "PUBLIC",
            "selected_brand_id": 144,
            "search_body": {
                "filters": {
                    "keywords_and_hashtags": "((new release 2025) AND (cosmetics))"
                }
            }
        }
    ]
}

Save the id value. This is your topic_id for all subsequent requests.

Already have a topic ID? Skip to Step 2.

Step 2: Map your parameters

Review the available parameters before making your API call:

Step 3: Make the API call

Send a PUT request using the parameters from Step 2 and the topic ID from Step 1. This example retrieves daily average engagements per post for topic 11423 on Instagram from May 1-7, with April 1-7 as the comparison period.

PUT https://dashboard.dashsocial.com/reports/data
  ?channels=INSTAGRAM
  &brand_ids=144
  &start_date=2025-05-01
  &end_date=2025-05-07
  &context_start_date=2025-04-01
  &context_end_date=2025-04-07
  &metrics=AVERAGE_ENGAGEMENTS_PER_POST
  &report_type=TOTAL_METRIC
body = {
  "listening": {
    "topic_ids": [11423]
  }
}

Sample response:

{
    "data": {
        "144": {
            "avatar": "https://cdn.dashsocial.com/avatars/2306810931.jpeg",
            "data_type": "BRAND",
            "name": "sunny.today",
            "user_has_access": true
        },
        "TOPIC_11423": {
            "data_type": "TOPIC",
            "metrics": {
                "AVERAGE_ENGAGEMENTS_PER_POST": {
                    "ALL_CHANNELS": {
                        "2025-05-01 00:00:00": 614,
                        "2025-05-02 00:00:00": 466,
                        "2025-05-03 00:00:00": 467,
                        "2025-05-04 00:00:00": 670,
                        "2025-05-05 00:00:00": 329,
                        "2025-05-06 00:00:00": 664,
                        "2025-05-07 00:00:00": 823
                    }
                }
            }
        },
        "metrics": {
            "AVERAGE_ENGAGEMENTS_PER_POST": {
                "ALL_CHANNELS": {
                    "2025-05-01 00:00:00": 614,
                    "2025-05-02 00:00:00": 466,
                    "2025-05-03 00:00:00": 467,
                    "2025-05-04 00:00:00": 670,
                    "2025-05-05 00:00:00": 329,
                    "2025-05-06 00:00:00": 664,
                    "2025-05-07 00:00:00": 823
                }
            }
        }
    },
    "product_category": "LISTENING"
}

Understanding the response: Topic data is nested under TOPIC_{id}. Brand metadata appears at the top level under the brand ID. Metric values are organized by date with daily breakdowns (e.g., May 1 had 614 average engagements, May 7 had 823).

Date format matters: Always use YYYY-MM-DD format for dates (e.g., 2025-05-01). Other formats will cause errors.

Metrics

Metric Name	Description	Metric API Name
Avg. Engagements	The estimated average number of engagements per post within this Topic that were published during the reporting period	`AVERAGE_ENGAGEMENTS_PER_POST`
Avg. Impressions	The estimated average number of impressions per post within this Topic during the reporting period. Impressions are estimated for Facebook, Instagram, X and Youtube.	`AVERAGE_IMPRESSIONS_PER_POST`
Avg. Mentions	The estimated number of posts published per day within this Topic during the reporting period	`AVG_MENTIONS_TOPIC`
Net Sentiment	The net sentiment of post captions within this Topic during the reporting period. Net sentiment shows the overall balance between positive and negative conversation.	`NET_SENTIMENT`
Engagements	The estimated number of engagements on posts within this Topic that were published during the reporting period	`TOTAL_ENGAGEMENTS_TOPIC`
Impressions	The estimated number of impressions on posts within this Topic during the reporting period. Impressions are estimated for Facebook, Instagram, X and Youtube.	`TOTAL_IMPRESSIONS_TOPIC`
Mentions	The estimated number of posts published within this Topic during the reporting period	`TOTAL_MENTIONS_TOPIC`

Metric Name	Description	Metric API Name
Avg. Engagements	The estimated average number of engagements per post within this Topic that were published during the reporting period	`AVERAGE_ENGAGEMENTS_PER_POST`
Avg. Mentions	The estimated number of posts published per day within this Topic during the reporting period	`AVG_MENTIONS_TOPIC`
Net Sentiment	The net sentiment of post captions within this Topic during the reporting period. Net sentiment shows the overall balance between positive and negative conversation.	`NET_SENTIMENT`
Engagements	The estimated number of engagements on posts within this Topic that were published during the reporting period	`TOTAL_ENGAGEMENTS_TOPIC`
Mentions	The estimated number of posts published within this Topic during the reporting period	`TOTAL_MENTIONS_TOPIC`

Metric Name	Description	Metric API Name
Avg. Engagements	The estimated average number of engagements per post within this Topic that were published during the reporting period	`AVERAGE_ENGAGEMENTS_PER_POST`
Avg. Impressions	The estimated average number of impressions per post within this Topic during the reporting period. Impressions are estimated for Facebook, Instagram, X and Youtube.	`AVERAGE_IMPRESSIONS_PER_POST`
Avg. Mentions	The estimated number of posts published per day within this Topic during the reporting period	`AVG_MENTIONS_TOPIC`
Net Sentiment	The net sentiment of post captions within this Topic during the reporting period. Net sentiment shows the overall balance between positive and negative conversation.	`NET_SENTIMENT`
Engagements	The estimated number of engagements on posts within this Topic that were published during the reporting period	`TOTAL_ENGAGEMENTS_TOPIC`
Impressions	The estimated number of impressions on posts within this Topic during the reporting period. Impressions are estimated for Facebook, Instagram, X and Youtube.	`TOTAL_IMPRESSIONS_TOPIC`
Mentions	The estimated number of posts published within this Topic during the reporting period	`TOTAL_MENTIONS_TOPIC`

Metric Name	Description	Metric API Name
Avg. Engagements	The estimated average number of engagements per post within this Topic that were published during the reporting period	`AVERAGE_ENGAGEMENTS_PER_POST`
Avg. Impressions	The estimated average number of impressions per post within this Topic during the reporting period. Impressions are estimated for Facebook, Instagram, X and Youtube.	`AVERAGE_IMPRESSIONS_PER_POST`
Avg. Mentions	The estimated number of posts published per day within this Topic during the reporting period	`AVG_MENTIONS_TOPIC`
Net Sentiment	The net sentiment of post captions within this Topic during the reporting period. Net sentiment shows the overall balance between positive and negative conversation.	`NET_SENTIMENT`
Engagements	The estimated number of engagements on posts within this Topic that were published during the reporting period	`TOTAL_ENGAGEMENTS_TOPIC`
Impressions	The estimated number of impressions on posts within this Topic during the reporting period. Impressions are estimated for Facebook, Instagram, X and Youtube.	`TOTAL_IMPRESSIONS_TOPIC`
Mentions	The estimated number of posts published within this Topic during the reporting period	`TOTAL_MENTIONS_TOPIC`

Metric Name	Description	Metric API Name
Avg. Engagements	The estimated average number of engagements per post within this Topic that were published during the reporting period	`AVERAGE_ENGAGEMENTS_PER_POST`
Avg. Mentions	The estimated number of posts published per day within this Topic during the reporting period	`AVG_MENTIONS_TOPIC`
Net Sentiment	The net sentiment of post captions within this Topic during the reporting period. Net sentiment shows the overall balance between positive and negative conversation.	`NET_SENTIMENT`
Engagements	The estimated number of engagements on posts within this Topic that were published during the reporting period	`TOTAL_ENGAGEMENTS_TOPIC`
Mentions	The estimated number of posts published within this Topic during the reporting period	`TOTAL_MENTIONS_TOPIC`

Metric Name	Description	Metric API Name
Avg. Engagements	The estimated average number of engagements per post within this Topic that were published during the reporting period	`AVERAGE_ENGAGEMENTS_PER_POST`
Avg. Impressions	The estimated average number of impressions per post within this Topic during the reporting period. Impressions are estimated for Facebook, Instagram, X and Youtube.	`AVERAGE_IMPRESSIONS_PER_POST`
Avg. Mentions	The estimated number of posts published per day within this Topic during the reporting period	`AVG_MENTIONS_TOPIC`
Net Sentiment	The net sentiment of post captions within this Topic during the reporting period. Net sentiment shows the overall balance between positive and negative conversation.	`NET_SENTIMENT`
Engagements	The estimated number of engagements on posts within this Topic that were published during the reporting period	`TOTAL_ENGAGEMENTS_TOPIC`
Impressions	The estimated number of impressions on posts within this Topic during the reporting period. Impressions are estimated for Facebook, Instagram, X and Youtube.	`TOTAL_IMPRESSIONS_TOPIC`
Mentions	The estimated number of posts published within this Topic during the reporting period	`TOTAL_MENTIONS_TOPIC`

Metric Name	Description	Metric API Name
Avg. Engagements	The estimated average number of engagements per post within this Topic that were published during the reporting period	`AVERAGE_ENGAGEMENTS_PER_POST`
Avg. Mentions	The estimated number of posts published per day within this Topic during the reporting period	`AVG_MENTIONS_TOPIC`
Net Sentiment	The net sentiment of post captions within this Topic during the reporting period. Net sentiment shows the overall balance between positive and negative conversation.	`NET_SENTIMENT`
Engagements	The estimated number of engagements on posts within this Topic that were published during the reporting period	`TOTAL_ENGAGEMENTS_TOPIC`
Mentions	The estimated number of posts published within this Topic during the reporting period	`TOTAL_MENTIONS_TOPIC`

Metric Name	Description	Metric API Name
Avg. Engagements	The estimated average number of engagements per post within this Topic that were published during the reporting period	`AVERAGE_ENGAGEMENTS_PER_POST`
Avg. Mentions	The estimated number of posts published per day within this Topic during the reporting period	`AVG_MENTIONS_TOPIC`
Net Sentiment	The net sentiment of post captions within this Topic during the reporting period. Net sentiment shows the overall balance between positive and negative conversation.	`NET_SENTIMENT`
Engagements	The estimated number of engagements on posts within this Topic that were published during the reporting period	`TOTAL_ENGAGEMENTS_TOPIC`
Mentions	The estimated number of posts published within this Topic during the reporting period	`TOTAL_MENTIONS_TOPIC`

Next steps

Use your time-series data to:

Visualize trends: Import data into Power BI, Tableau, or Looker to create executive dashboards
Identify momentum shifts: Compare daily or monthly metrics to spot when conversations accelerate or decline
Measure campaign impact: Track metrics before, during, and after campaigns to quantify effectiveness
Compare time periods: Use context dates to benchmark current performance against historical data

Data freshness: Metric updates vary by post age. Recently published posts refresh more frequently than older content. Focus on data from the last 90 days for the most accurate reporting.

Other social listening reports: This guide covers graph reports for time-series data. Social listening also supports:

Metric reports for aggregated totals
Social Listening API for detailed post-level data

Get Started

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Social Listening

Community

Integration

MCP Server

Track social listening trends with graph report

Use cases

Campaign momentum tracking

Brand health monitoring

Competitive trend analysis

Executive reporting

Before you start

Implementation

Step 1: Get your topic ID

Key query parameters

Step 2: Map your parameters

Step 3: Make the API call

Metrics

Next steps

​Use cases

Campaign momentum tracking

Brand health monitoring

Competitive trend analysis

Executive reporting

​Before you start

​Implementation

​Step 1: Get your topic ID

​Key query parameters

​Step 2: Map your parameters

​Step 3: Make the API call

​Metrics

​Next steps

Use cases

Before you start

Implementation

Step 1: Get your topic ID

Key query parameters

Step 2: Map your parameters

Step 3: Make the API call

Metrics

Next steps