Overview

Social Searcher is a social media monitoring and search platform that enables real-time searching across major social networks including Twitter/X, Facebook, Instagram, YouTube, Reddit, Tumblr, Flickr, VKontakte, and more. Unlike platform-native search tools that only index their own content, Social Searcher provides a unified search interface across multiple platforms simultaneously, eliminating the need for investigators to maintain accounts on each platform or navigate their individual search interfaces.

The platform goes beyond simple keyword matching by providing sentiment analysis, trend detection, and user analytics for discovered content. Each search result is annotated with sentiment polarity (positive, neutral, negative), engagement metrics, and temporal patterns. This makes Social Searcher valuable not just for finding content, but for understanding the context and impact of social media activity around specific topics, organizations, or individuals.

For OSINT investigators, Social Searcher fills a critical gap: searching across multiple social platforms from a single interface without requiring accounts on each platform. This is particularly valuable for brand monitoring, person investigation, and tracking public discussions about specific topics, organizations, or events. The cross-platform search capability enables comprehensive social media intelligence collection that would otherwise require manual querying of each platform individually.

Data Sources and Coverage

Social Searcher indexes content from a broad range of social media platforms, with coverage depth varying by platform API availability and terms of service. The platform maintains direct integrations with major social networks and supplements these with web crawling for publicly accessible content.

Data Type	Description	Coverage
Posts/Messages	Text content from social media posts across platforms	Multi-platform
Sentiment	Positive/neutral/negative classification per post	Automated NLP
Authors	Username, profile URL, follower count, platform	Where available
Engagement	Likes, shares, comments, retweets per post	Platform-specific
Timestamps	Post creation time with timezone	Precise temporal data
Media	Images, videos, links shared in posts	Referenced content
Hashtags	Trending and associated hashtags	Tag-based discovery
Platforms	Twitter/X, Facebook, Instagram, YouTube, Reddit, VK, Tumblr	10+ platforms

Multi-Platform Search

Search query: "prismatic platform"
    |
    v
Social Searcher dispatches to: Twitter + Facebook + Reddit + YouTube + Instagram + VK
    |
    v
Aggregated results with sentiment, engagement, and temporal analysis
    |
    v
Prismatic ingests for entity monitoring and threat intelligence

The cross-platform aggregation normalizes the diverse data formats from different social networks into a consistent schema, enabling unified analysis across platforms. Engagement metrics are platform-specific but are normalized for comparative analysis where possible.

Technical Architecture

The Prismatic Platform integrates Social Searcher through a REST API adapter designed for both real-time monitoring and historical research workflows. The adapter implements a polling-based monitoring system that checks for new mentions of monitored entities at configurable intervals.

The sentiment analysis pipeline ingests Social Searcher's per-post sentiment classifications and aggregates them into entity-level sentiment trends over time. Significant sentiment shifts (spike detection) trigger automated alerts, enabling security and communications teams to respond rapidly to emerging reputation issues.

The adapter implements intelligent rate limit management across the daily quota allocation, prioritizing high-priority entity monitoring over routine scanning. When daily limits approach, the system automatically reduces polling frequency for lower-priority monitored entities while maintaining full coverage for critical monitoring targets.

Historical data access enables temporal analysis of social media discourse around entities, identifying patterns in discussion volume, sentiment trajectory, and platform-specific engagement dynamics. This historical context is essential for distinguishing between normal social media activity patterns and anomalous spikes that may indicate PR crises, security incidents, or coordinated campaigns.

API Integration

Social Searcher provides social media intelligence for the Prismatic platform's entity monitoring and reputation analysis pipelines.

# Search across all platforms
{:ok, results} = SocialSearcher.search("prismatic cybersecurity")
# => %{
#   posts: [
#     %{text: "Great new OSINT platform...", network: "twitter",
#       user: %{name: "SecurityResearcher", followers: 15000},
#       sentiment: :positive, posted: ~U[2025-12-01 10:00:00Z],
#       engagement: %{likes: 45, retweets: 12, replies: 3}},
#     %{text: "Review of prismatic...", network: "reddit",
#       user: %{name: "netsec_user", subreddit: "r/netsec"},
#       sentiment: :neutral, posted: ~U[2025-11-28 15:30:00Z],
#       engagement: %{upvotes: 89, comments: 23}}
#   ],
#   total_results: 156,
#   sentiment_breakdown: %{positive: 0.45, neutral: 0.40, negative: 0.15},
#   top_platforms: [twitter: 78, reddit: 42, youtube: 21]
# }

# Platform-specific search
{:ok, tweets} = SocialSearcher.search("target query", network: :twitter)

# Search by user
{:ok, posts} = SocialSearcher.search_user("username", network: :twitter)

# Sentiment analysis for a topic
{:ok, sentiment} = SocialSearcher.analyze_sentiment("company name",
  period: :last_30_days
)

# Monitor mentions in real-time
{:ok, stream} = SocialSearcher.monitor("brand name",
  alert_on: :negative_sentiment,
  networks: [:twitter, :reddit, :facebook]
)

# Get trending topics
{:ok, trends} = SocialSearcher.trending(country: "CZ", network: :twitter)

# Historical search with date range
{:ok, archive} = SocialSearcher.search("topic",
  from: ~D[2025-01-01],
  to: ~D[2025-12-31]
)

defmodule PrismaticIntelligence.Social.ReputationMonitor do
  @moduledoc """
  Monitors social media for entity mentions and sentiment shifts.
  Feeds into Perimeter security ratings and risk assessments.
  """

  def monitor_entity(entity_name) do
    with {:ok, social_data} <- SocialSearcher.search(entity_name),
         {:ok, news_data} <- NewsApi.search(entity_name),
         {:ok, pipl_data} <- get_person_social(entity_name) do
      {:ok, %{
        entity: entity_name,
        social_mentions: length(social_data.posts),
        sentiment: social_data.sentiment_breakdown,
        sentiment_trend: calculate_trend(social_data),
        platforms: social_data.top_platforms,
        news_mentions: length(news_data.articles),
        risk_indicators: identify_risk_signals(social_data),
        monitored_at: DateTime.utc_now()
      }}
    end
  end

  defp identify_risk_signals(social_data) do
    signals = []
    signals = if social_data.sentiment_breakdown.negative > 0.4, do: [:high_negative_sentiment | signals], else: signals
    signals = if spike_detected?(social_data), do: [:mention_spike | signals], else: signals
    signals
  end
end

Use Cases

Brand Monitoring

Track mentions of company, product, or executive names across social platforms with real-time alerting
Detect negative sentiment spikes that may indicate PR crises, data breaches, or service outages
Monitor competitor mentions and industry discussions for competitive intelligence
Measure the reach and engagement of brand communications across platforms

Person Investigation

Discover social media presence from name or known username across multiple platforms simultaneously
Analyze posting patterns, sentiment, and engagement for behavioral profiling
Cross-reference with Pipl for comprehensive person profiles connecting social accounts to real identities
Track subject activity across platforms for ongoing investigation monitoring

Threat Intelligence

Monitor discussions about vulnerabilities and exploits on security-focused social platforms
Track threat actor communications on public platforms (Twitter, Reddit, forums)
Identify data breach announcements and leaked credential discussions in near real-time
Monitor for credential dump announcements and initial access broker advertisements

Reputation Risk Assessment

Quantify social media sentiment as a component of entity risk scoring
Track sentiment trends over time to identify emerging reputation issues before they escalate
Compare entity sentiment profiles against industry benchmarks for contextual risk assessment

Data Quality

Social Searcher data quality depends on the accessibility and completeness of content from each indexed social platform. Platform API changes and rate limits can affect coverage depth.

Quality Dimension	Assessment	Notes
Platform Coverage	Good -- 10+ major platforms	Subject to API availability
Sentiment Accuracy	Good -- automated NLP classification	May miss sarcasm and context
Timeliness	High -- near real-time for most platforms	Some platform indexing lag
Engagement Data	Good -- platform-specific metrics	Not normalized across platforms
Historical Depth	Variable -- depends on tier and platform	Premium tier has deeper archive
Author Attribution	Good -- username and profile data	Public profiles only

Rate Limits and Access

Tier	Searches/Day	Features
Free	100	Basic search, limited results, no API
Basic	600	API access, sentiment analysis
Premium	3,000	Historical data, monitoring alerts
Enterprise	Unlimited	Bulk API, custom integration, full archive

API key required for programmatic access. Free web search available without registration.

Platform Integration

Within the Prismatic Platform, Social Searcher provides the social media intelligence layer that complements traditional news monitoring from NewsAPI and GDELT. Together, these sources create a unified media intelligence capability spanning both traditional and social media.

Social media sentiment data feeds into the Prismatic Perimeter security rating through the reputation component, where persistent negative sentiment or sudden sentiment shifts contribute to the overall entity risk assessment.

NABLA Compliance

Social Searcher integration addresses NABLA requirements with particular attention to the quality characteristics of social media data. The Signal Plurality axiom is naturally supported by cross-platform search, where corroborating signals across independent social networks strengthen confidence. The Provenance Mandatory axiom is met through attribution to specific posts, users, and platforms.

Contradiction Preservation is maintained when sentiment analysis shows mixed signals across platforms, preserving the complexity of public discourse rather than collapsing it into a single sentiment score.

Performance

Metric	Target	Typical
Cross-platform search	< 3s	1-2s
Platform-specific search	< 2s	500ms-1.5s
Sentiment analysis	< 5s	2-3s
Monitoring cycle (20 entities)	< 10min	5-7min
Daily quota utilization	< 85%	60-75%

Pipl - Deep people search with social profile aggregation
Clearbit - Person and company enrichment from identifiers
LinkedIn Sales Navigator - Professional network intelligence
GDELT - Global news and event monitoring
NewsAPI - News article aggregation and search
OSINT Core - Core OSINT framework and adapter layer
Prismatic Perimeter - Social media reputation in security ratings

Connect & Contribute

Created by Tomáš Korcak (korczis) | Open Source under GHL

GitHub | GitLab | LinkedIn | Contact
Developer Portal | Architecture | Meet the Creator

Social Searcher

Capabilities

Try Social Searcher

Overview

Data Sources and Coverage

Multi-Platform Search

Technical Architecture

API Integration

Use Cases

Brand Monitoring

Person Investigation

Threat Intelligence

Reputation Risk Assessment

Data Quality

Rate Limits and Access

Platform Integration

NABLA Compliance

Performance

Connect & Contribute

Intelligence Network

Related Content

Agent Ecosystem

Applications

Doctrine

Social Searcher

Capabilities

Try Social Searcher

Overview

Data Sources and Coverage

Multi-Platform Search

Technical Architecture

API Integration

Social Media Intelligence Pipeline

Use Cases

Brand Monitoring

Person Investigation

Threat Intelligence

Reputation Risk Assessment

Data Quality

Rate Limits and Access

Platform Integration

NABLA Compliance

Performance

Related Resources

Connect & Contribute

Intelligence Network

Related Content

Agent Ecosystem

Applications

Doctrine