Subject
Media & Communication
Volume, attention, framing and tone: how coverage is counted, and how to read the counts.
Tutorials
- Reading Media Volume (声量): What a Mention Count Does and Does Not Tell You
Mention volume, called 声量 in Chinese media monitoring, looks like a plain count. Five choices decide its value, and the same two weeks can be +50%, +23% or no change, depending on how you count.
- Counting Stories, Not Copies: Near-Duplicates and Syndicated News
News travels by copy. To count what was reported, rather than how often it was reprinted, group near-identical texts. A walk-through of shingles, similarity scores and the limits of the method.
Glossary terms
- Agenda-setting
The finding that topics the media cover most are the topics the public comes to rate as most important: media shape what people think about, not what they think.
- Cohen's Kappa
How much two raters agree beyond what chance alone would produce: 1 is perfect, 0 is no better than chance.
- Content Analysis
A method that turns texts or images into countable categories using explicit coding rules, so that claims about content can be checked and repeated.
- Corroboration
Confirming a claim with evidence independent of the original source. Reports that trace back to the same origin count as one.
- Event Detection
Finding, in a stream of documents, the moments when something new has happened, usually as a burst of stories about the same thing.
- Framing
Choosing which aspects of a situation to emphasise so as to suggest a particular problem, cause or remedy. The same facts can be framed in different ways.
- Mention Volume
How many times a topic, brand or person is mentioned in a defined set of sources over a period. Its meaning depends entirely on how the count is defined.
- Named Entity Recognition (NER)
Finding mentions of real-world things in text, such as people, organisations and places, and labelling their type. Linking each mention to one identifier is a separate step.
- Near-duplicate Detection
Finding documents that are almost, but not exactly, the same, such as a news story republished with a new headline, by comparing fingerprints of their word sequences.
- Sentiment Analysis
Automatically classifying text by the attitude it expresses, usually positive, negative or neutral. It reads wording, not truth, and has well-known blind spots.
- Share of Voice (SOV)
One party's mentions as a share of all mentions of the parties being compared. It is relative, so it can fall while your own mentions rise.
- Syndicated Content
Material produced once and published by many outlets, such as a news-agency story. Counting every publication overstates how many independent sources reported something.
- Tokenization
Splitting text into the units a search or analysis system works with, usually words. It decides what can match, and in Chinese finding the word boundaries is a task of its own.