Social Media Field Matrix

Purpose

The Social Media Field Matrix documents how metrics and fields exposed by different social media platforms map to the organization's canonical data model.

It separates platform specific representations from canonical organizational definitions, allowing data from X, LinkedIn, Instagram, Facebook, and TikTok to be consolidated without losing important differences in meaning.

The detailed source field inventory is maintained separately as a machine readable artifact and contains the technical metadata required for ingestion and implementation.

Cross Platform Canonical Mapping

Platform	Source Field	Canonical Definition	Mapping	Confidence	Reason
X	public_metrics.followers_count	social.follower_count	Direct	High	Same basic audience count
X	public_metrics.following_count	social.following_count	Direct	High	Number of accounts followed
X	public_metrics.tweet_count	social.x.tweet_count	Platform Specific	High	Includes retweets and does not cleanly represent generic published content
X	public_metrics.impression_count	social.impressions	Direct	High	Views or impressions of content
X	public_metrics.like_count	social.like_count	Direct	High	Like interaction
X	public_metrics.retweet_count	social.repost_count	Semantic	Medium	Retweet is treated as a form of repost, although platform terminology differs
LinkedIn	followerCount	social.follower_count	Direct	High	Same audience concept
LinkedIn	totalShareStatistics.shareCount	social.share_count	Direct	High	Share interaction aggregated over a defined period
LinkedIn	totalShareStatistics.impressionCount	social.impressions	Direct	High	Impressions over a bounded period
LinkedIn	impressionCount	social.impressions	Direct	High	Post level impression measure
Instagram	followers_count	social.follower_count	Direct	High	Same audience concept
Instagram	like_count	social.like_count	Direct	High	Like interaction
Instagram	impressions	social.impressions	Direct	High	Total content impressions
Instagram	reach	social.reach	Direct	High	Unique accounts reached
Facebook	followers_count	social.follower_count	Direct	High	Same audience concept
Facebook	fan_count	social.page_like_count	Platform Specific	High	Page Likes are not equivalent to followers
Facebook	post_impressions_unique	social.reach	Direct	High	Represents unique people reached
TikTok	follower_count	social.follower_count	Direct	High	Same audience concept
TikTok	view_count	social.video_view_count	Semantic	High	Video plays are a content specific view measure

Mapping Types

The matrix uses the following mapping classifications.

Direct

The source field and canonical definition have substantially the same meaning.

Example:

Instagram followers_count
        ↓
social.follower_count

Semantic

The source field is mapped to a broader canonical concept whose meaning is sufficiently compatible, but whose terminology or precise semantics differ.

Example:

X retweet_count
        ↓
social.repost_count

Semantic mappings should be reviewed when calculating cross platform metrics.

Platform Specific

The source field has meaning that should remain specific to the originating platform.

Example:

Facebook fan_count
        ↓
social.page_like_count

Platform specific definitions should not be combined with a generic canonical metric merely for the sake of cross platform consistency.

Conditional

A mapping is valid only under defined conditions or requires additional context before it can be treated as equivalent.

Conditional mappings should document those conditions in mapping_notes.

Unresolved

The source field has been identified but no canonical mapping has yet been approved.

Unresolved fields should remain visible in the source inventory rather than being forced into an unsuitable canonical definition.

Canonical Metrics Identified

The current field mapping identifies the following candidate canonical social media metrics:

Audience

social.follower_count
social.following_count

Exposure

social.impressions
social.reach
social.video_view_count

Engagement

social.like_count
social.share_count
social.repost_count

Platform Specific

social.x.tweet_count
social.page_like_count

These are canonical metrics, not necessarily KPIs.

A metric becomes a KPI only when the organization explicitly designates it as an important measure of performance against an objective or decision.

Important Semantic Distinctions

Followers vs Page Likes

social.follower_count and social.page_like_count are intentionally separate.

A Facebook Page Like should not automatically be treated as a follower because the underlying platform concepts are different.

Impressions vs Reach

social.impressions represents the total number of content exposures or views.

social.reach represents the number of unique accounts or people exposed to the content.

One person can therefore contribute multiple impressions while contributing only once to reach.

Source Metrics vs Canonical Metrics

A platform field does not become canonical simply because it exists in an API.

For example:

Facebook
    fan_count
        ↓
social.page_like_count

rather than:

Facebook
    fan_count
        ↓
social.follower_count

Canonical definitions represent organizational meaning rather than source system terminology.

Measurement Considerations

The same canonical metric may have different measurement characteristics depending on its source.

Examples include:

Snapshot
    social.follower_count

Cumulative
    social.like_count

Period Aggregate
    social.impressions

Unique Exposure
    social.reach

These distinctions must be preserved when metrics are stored and aggregated.

A cumulative lifetime value should not automatically be summed across time periods. A point in time snapshot should not be treated as an additive measure. Unique measures such as reach are generally non additive across overlapping content.

The metric definitions will specify the permitted aggregation behaviour in more detail.

Source Field Inventory

The complete platform source field inventory is maintained as a machine readable CSV and serves as the implementation reference for this matrix.

Download the Social Media Source Field Inventory

The inventory contains the technical metadata for each source field, including:

• Platform and source object
• Source field
• Data type
• Grain
• Measurement type
• Time semantics
• Historical API availability
• Availability
• Source notes
• Canonical mapping
• Mapping type
• Mapping confidence
• Mapping notes

This page provides the human readable semantic interpretation of that inventory. The CSV provides the detailed source level representation.

Evolution

This matrix is expected to evolve as additional platform fields are discovered and as the organization's understanding of cross platform semantics improves.

A source field should not be mapped to an existing canonical definition merely because the names appear similar.

When semantic equivalence is uncertain, the field should remain platform specific or unresolved until the meaning can be established with sufficient confidence.

The objective is not to make every platform identical.

The objective is to establish a consistent organizational vocabulary while preserving meaningful differences between source systems.