Newsmap: geographical news classifier
Semi-supervised Bayesian model for geographical document classification. Its online version has been working since 2011. It has first been in Python, but recently implemented in R. This program automatically construct a large geographical dictionary from a corpus of news stories for accurate classification. Currently, the newsmap package contains seed dictionaries for English, German, Spanish, Japanese, Russian, Chinese documents.
The detail of the algorithm is explained in Newsmap: semi-supervised approach to geographical news classification. newsmap has also been used in recent social scientific studies:
- Kohei Watanabe, 2017. "Measuring News Bias: Russia’s Official News Agency ITAR-TASS’s Coverage of the Ukraine Crisis", European Journal Communication
- Kohei Watanabe, 2017. "The spread of the Kremlin’s narratives by a western news agency during the Ukraine crisis", Journal of International Communication
- Tomila Lankina and Kohei Watanabe. 2017. "Russian Spring’ or ‘Spring Betrayal’? The Media as a Mirror of Putin’s Evolving Strategy in Ukraine", Europe-Asia Studies
Please contact Kohei Watanabe or issue a pull request if you want your publication included in this list.
How to install
newsmap is available on CRAN since the version 0.6. You can install the package using R Studio GUI or the command.
If you want to the latest version, please install by running this command in R. You need to have devtools installed beforehand.
In this example, using a text analysis package quanteda for preprocessing of textual data, we train a geographical classification model on a corpus of news summaries collected from Yahoo News via RSS in 2014.
Download example data
Train Newsmap classifier
library(newsmap) library(quanteda) ## Package version: 1.3.9 ## Parallel computing: 2 of 8 threads used. ## See https://quanteda.io for tutorials and examples. ## ## Attaching package: 'quanteda' ## The following object is masked from 'package:utils': ## ## View # Load data data <- readRDS('~/yahoo-news.RDS') data$text <- paste0(data$head, ". ", data$body) data$body <- NULL corp <- corpus(data, text_field = 'text') # Custom stopwords month <- c('January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December') day <- c('Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday') agency <- c('AP', 'AFP', 'Reuters') # Select training period sub_corp <- corpus_subset(corp, '2014-01-01' <= date & date <= '2014-12-31') # Tokenize toks <- tokens(sub_corp) toks <- tokens_remove(toks, stopwords('english'), valuetype = 'fixed', padding = TRUE) toks <- tokens_remove(toks, c(month, day, agency), valuetype = 'fixed', padding = TRUE) # Seed dictionaries supplied by this package # English: data_dictionary_newsmap_en # German: data_dictionary_newsmap_de # Japanese: data_dictionary_newsmap_ja # Spanish: data_dictionary_newsmap_es # Russian: data_dictionary_newsmap_ru label_toks <- tokens_lookup(toks, data_dictionary_newsmap_en, levels = 3) # level 3 is countries label_dfm <- dfm(label_toks) feat_dfm <- dfm(toks, tolower = FALSE) feat_dfm <- dfm_select(feat_dfm, selection = "keep", '^[A-Z][A-Za-z1-2]+', valuetype = 'regex', case_insensitive = FALSE) # include only proper nouns to model feat_dfm <- dfm_trim(feat_dfm, min_count = 10) ## Warning in dfm_trim.dfm(feat_dfm, min_count = 10): min_count is deprecated, ## use min_termfreq model <- textmodel_newsmap(feat_dfm, label_dfm) # Features with largest weights coef(model, n = 7)[c("us", "gb", "fr", "br", "jp")] ## $us ## US WASHINGTON American Washington Americans YORK ## 10.733869 10.031534 9.773099 9.496846 8.234697 6.951198 ## States ## 6.285434 ## ## $gb ## British London LONDON Britain Britain's UK Briton ## 10.939468 10.653923 10.647544 10.396778 9.754031 9.711121 7.533754 ## ## $fr ## French France PARIS Paris Valls Frenchman CANNES ## 11.348094 11.322555 10.448944 10.259995 8.005111 7.838057 7.742747 ## ## $br ## Brazil Brazilian SAO PAULO RIO JANEIRO Rio ## 11.63429 10.33501 10.28738 10.28285 10.21237 10.20553 10.09799 ## ## $jp ## Japan Japanese TOKYO Tokyo Abe Abe's Shinzo ## 11.752176 10.938679 10.795813 10.101658 8.653831 8.065616 7.983856
Predict geographical focus of texts
pred_data <- data.frame(text = texts(sub_corp), country = predict(model))
|text63||'08 French champ Ivanovic loses to Safarova in 3rd. PARIS (AP) - Former French Open champion Ana Ivanovic lost in the third round Saturday, beaten 6-3, 6-3 by 23rd-seeded Lucie Safarova of the Czech Republic.||fr|
|text68||Up to $1,000 a day to care for child migrants. More than 57,000 unaccompanied children, mostly from Central America, have been caught entering the country illegally since last October, and President Barack Obama has asked for $3.7 billion in emergency funding to address what he has called an "urgent humanitarian solution." "One of the figures that sticks in everybody's mind is we're paying about $250 to $1,000 per child," Senator Jeff Flake told reporters, citing figures presented at a closed-door briefing by Homeland Security Secretary Jeh Johnson. Federal authorities are struggling to find more cost-effective housing, medical care, counseling and legal services for the undocumented minors. The base cost per bed was $250 per day, including other services, Senator Dianne Feinstein said, without providing details.||us|
|text69||1,000 DRC ex-rebels break out of Uganda camp: army. About 1,000 former fighters from a former Democratic Republic of Congo rebel group broke out Tuesday from a camp where they being held in Uganda just as soldiers were about to repatriate them, the Ugandan army said. "A thousand rebels from the M23 (group) have escaped" from the camp in Bihanga, about 300 kilometres (190 miles) southwest of the Ugandan capital Kampala, a spokesman for the Ugandan army said on the official Twitter account.||ug|
|text73||1,000 killed in Boko Haram conflict this year. More than 1,000 people have been killed so far this year in three states in northeastern Nigeria worst hit by Boko Haram violence, according to the country's main relief organisation. The National Emergency Management Agency (NEMA) figures are the starkest indication yet of the increase in bloodshed in Borno, Adamawa and Yobe that have caused growing concern. NEMA said in a presentation in Abuja on Tuesday that people living in the states were "caught up in an intensifying conflict", which has been raging since 2009. Violence has increased in northeastern Nigeria since the new year, including a high-profile attack on a boarding school in Yobe, which saw dozens of students slaughtered in their beds.||ng|
|text78||1,000 migrants repulsed at Spanish border. MADRID (AP) - Officials say around 1,000 migrants of sub-Saharan origin have failed in an attempt to get over Spain's three-tier barbed-wire border fence separating its North African enclave of Melilla from Morocco in a bid to enter Europe.||es|
|text79||Some 1,000 migrants try to reach Spain from Africa. MADRID (AP) - Some 700 migrants stormed a border fence to try to enter Spain's northwest African enclave city of Melilla from Morocco on Tuesday while the sea rescue service said it had picked up some 500 others trying to enter the country clandestinely by crossing the Strait of Gibraltar in boats, officials said.||es|