COVID-19 Outbreak through Tweeters' Words: Monitoring Italian Social Media Communication about COVID-19 with Text Mining and Word Embeddings.
Andrea SciandraPublished in: ISCC (2020)
Keyphrases
- text mining
- social media
- text documents
- n gram
- related words
- text corpus
- text corpora
- word sense disambiguation
- word pairs
- natural language text
- early warning
- english words
- word recognition
- word meaning
- natural language processing
- unknown words
- text classification
- word segmentation
- linguistic knowledge
- keywords
- multiword
- short messages
- word frequencies
- lexical information
- linguistic information
- word similarity
- latent topics
- topic models
- spoken document retrieval
- information extraction
- distributional clustering
- chinese word segmentation
- monitoring system
- stop words
- syntactic categories
- word level
- word spotting
- word co occurrence
- social media data
- vector space
- disease outbreaks
- social networks
- lexical features
- data mining
- compound words
- word meanings
- co occurrence
- training corpus
- text categorization
- word sense
- control center
- named entities
- query words
- handwritten words
- translation model
- low dimensional
- textual data
- user generated content
- sentiment analysis
- numeral strings
- punctuation marks
- word frequency
- public health
- topic modeling
- latent dirichlet allocation
- semantic relations
- semantic similarity
- document clustering
- machine learning