Breaking News
A news event of significant importance that develops urgently and is reported as it unfolds. Breaking news typically has high virality potential because readers want immediate, real-time updates.
Example: "Major political scandal breaks; PM faces calls to resign"
Category
Tagtaly's four-tier classification system: Politics (government/policy), Lifestyle (health/crime/weather), Entertainment (celebrity/media), Money (business/finance). Every article is categorized based on primary focus.
Example: A healthcare story about new treatment breakthroughs is categorized as "Lifestyle" because it focuses on health, not policy.
Coverage Distribution
The percentage breakdown of articles across the four categories. Shows what types of stories dominate the news cycle on any given day.
Example: "Today's coverage: Politics 45%, Lifestyle 25%, Entertainment 20%, Money 10%" reveals politics is dominating news.
Data Deduplication
The process of removing duplicate articles from the database. Tagtaly uses MD5 hashing of article URLs to identify and exclude duplicates, ensuring each story is counted only once.
Example: If 3 outlets republish the same story, deduplication ensures it's counted as 1 unique story, not 3.
Emotional Valence
The inherent emotional quality of language—whether words tend toward positive or negative. High valence words (brilliant, excellent) are positive; low valence words (terrible, horrible) are negative.
Example: "Brilliant economic growth" has high positive valence; "Economic collapse feared" has high negative valence.
Engagement Rate
A measure of how much audience interaction a story generates (clicks, shares, comments). High-virality stories typically have high engagement rates on social media.
Example: A story with 50,000 shares has higher engagement than one with 500 shares.
Headline Analysis
The automated examination of article headlines to extract information about sentiment, topic, urgency, and keywords. Most sentiment and virality detection starts with headline analysis.
Example: "Record-breaking unemployment" headline triggers: record detection algorithm + negative sentiment score.
Impact Score
A metric measuring how significantly a story affects public discourse, policy, or business. Not the same as virality—a policy change might have high impact but low virality.
Example: A regulatory change with low social media shares still has high impact on businesses.
Live Feed
Tagtaly's real-time article stream showing the latest stories in your selected category or search. Updated hourly with newest articles from tracked sources.
Example: Filter live feed to "Politics" to see only political stories as they're published.
Media Bias
Differences in how outlets cover the same story. Bias reflects editorial priorities, not necessarily truth. Tagtaly tracks coverage disparities to reveal bias.
Example: BBC covers election 3 ways; Guardian covers it 12 ways = Editorial bias toward Guardian coverage.
Neutral Sentiment
Articles with sentiment scores between -0.25 and +0.25. Typically factual, objective reporting without strong emotional language.
Example: "Parliament votes on new legislation; results expected next week" is neutral reporting.
Negative Polarity
Articles with sentiment scores below -0.25. Contain predominantly critical, concerning, or pessimistic language.
Example: "Healthcare crisis deepens" has negative polarity.
Outlet
A news source or publication. Tagtaly tracks outlets (BBC, Guardian, Sky, Independent, Washington Post) to analyze coverage patterns and bias.
Example: "BBC is the outlet breaking the story; other outlets are following their coverage."
Polarity Score
The numerical sentiment value assigned to an article, ranging from -1.0 (very negative) to +1.0 (very positive). Calculated by TextBlob.
Example: "Record achievement in renewable energy" has polarity score of +0.75.
Positive Polarity
Articles with sentiment scores above +0.25. Contain predominantly celebratory, optimistic, or constructive language.
Example: "Amazing breakthrough in medical research" has positive polarity.
Political Mention Tracking
Virality algorithm that counts mentions of key political figures. Sudden spikes indicate political news with high viral potential.
Example: PM mentioned in 60 articles today vs. normal 8-10 = Major political story.
Record Number Detection
Virality algorithm that identifies stories with superlatives ("record," "highest," "lowest," "unprecedented"). These phrases indicate notable, newsworthy stories.
Example: "Record-breaking heatwave" or "Lowest unemployment in 30 years" trigger this algorithm.
RSS Feed
Really Simple Syndication. A data feed format that outlets use to publish article metadata (headlines, summaries, URLs). Tagtaly uses RSS feeds to collect article data.
Example: BBC's RSS feed publishes new articles every few minutes; Tagtaly reads and processes them.
Sentiment Shift
A significant change in the emotional tone of coverage for a topic over a short period. Indicates a major development or change in public mood.
Example: Politics sentiment drops from +0.3 to -0.7 overnight = Major negative political development.
Story Trend
The trajectory of a story's virality, sentiment, and coverage over time. Understanding trends helps editors predict what's developing.
Example: Virality score rising 6 → 12 → 18 shows a story gaining momentum and likely to peak soon.
TextBlob
A natural language processing library that analyzes sentiment. Tagtaly uses TextBlob to scan article text and assign polarity scores.
Example: TextBlob scans "Excellent breakthrough" and assigns high positive polarity.
Topic
A subject area within a category. Examples: UK Politics, US Politics, Health, Crime, Celebrity, Finance. Topics are more granular than categories.
Example: "Health & Safety" is a topic within the Lifestyle category.
Topic Surge
A sudden, significant increase in article volume for a specific topic. Week-over-week comparison. Indicates breaking news or emerging trend.
Example: Politics articles jump from 30/day to 120/day = 300% surge.
Topic Surge Detection
Virality algorithm that identifies sudden increases in coverage volume for a topic by comparing week-over-week growth.
Example: Health topic jumps 50% week-over-week = Strong viral signal.
Topic Timeline
A chart showing when articles on a specific topic are published throughout the day. Reveals when outlets focus coverage attention.
Example: Morning peak at 7 AM shows overnight story reporting; evening peak at 6 PM shows analysis pieces.
Trending Topic
A topic with rapidly increasing article volume and virality potential. Topics trending are more likely to dominate social media and public conversation.
Example: A topic with virality score 15+ and rising volume is trending.
Virality
The potential for a story to spread widely on social media and dominate public conversation. High-virality stories are shared frequently, commented on, and discussed.
Example: Celebrity scandal or political scandal typically have high virality.
Virality Score
A numerical rating (0-20) predicting story viral potential. Combines 5 detection algorithms. Higher scores = higher likelihood of trending.
Example: Score 18/20 indicates very strong viral potential; score 4/20 indicates low potential.
Viral Potential
The likelihood a story will achieve high social media engagement and public attention. Determined by multiple signals: topic surge, sentiment, outlets, keywords.
Example: A story checking all viral signals (surge + records + sentiment shift) has high viral potential.
Week-over-Week Comparison
Comparing this week's data against the previous week. Used to detect topic surges and identify what's changed in news priorities.
Example: "This week's Politics coverage is 180% higher than last week = Major news cycle shift."
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