Concert-Diary has been advertising classical concerts since 2000, mainly in the UK, and (unlike some listings websites) allows you to go back and look at historic data. Concerts can be classified under several headings – one of which is “Christmas”, so I thought it would be interesting to look at this century’s Christmas concerts.
Continue reading →
The Google Books Ngram Viewer is a powerful tool for analysing historical text data. It uses the enormous corpus of books scanned by Google to analyse the frequency of words and phrases over time. An n-grams is just a combination of words – so a single word is a 1-gram, a pair of words a 2-gram, etc. The Google viewer has data up to 5-grams.
This has potential uses in many fields – including musicology. Here we will use the ngram viewer to analyse the rise and fall of ragtime music.
Continue reading →
Here is a short festive quiz based on the lyrics of the top 30 carols on the carols.org.uk website. The challenge is to identify the carol from words that appear only in the lyrics of that carol and no other. So “merrily”, for example, only appears in one carol (clue: Ding Dong). It is just for fun – there is no prize other than a smug feeling and whatever you decide to reward yourself with!
Continue reading →
Many British buildings are adorned with plaques, marking the birthplace or residence of a famous person, or the site of a significant event. Details of these plaques are available in an online database, and I thought it would be interesting to see how many of them have a musical connection.
Continue reading →
In this previous post in the series, we used capitalisation to identify proper nouns (names, places, etc) in our dataset of song lyrics. Other parts of speech – verbs, adjectives, etc – are not so easy to identify, although software exists to do just that.
Continue reading →
Previously, we have looked at repetition in our dataset of song lyrics. This seventh article in the series considers a related issue – rhyming patterns. We are only interested here in the last word of each line – i.e. the string of characters between the last space and the end-of-line character \n.
This is the sixth in a series of articles looking at different ways of analysing a dataset of song lyrics. In this article we will be venturing into hyperspace to explore the differences and similarities between artists, in terms of the words they use in their songs.
Continue reading →
In a later post in this series of articles analysing a dataset of song lyrics, I will consider the more general question of identifying parts-of-speech (nouns, verbs, adjectives, etc.), which can greatly expand what can be learned from statistical text analysis. However, in this article, I will focus on a particular part of speech: proper nouns.
Continue reading →In this fourth article in the series looking at our song lyrics dataset, we will begin to consider the meaning of the lyrics, rather than just treating the words as abstract objects. A simple technique for quantifying the meaning of texts is known as ‘sentiment analysis’.
Continue reading →
We all know that a good song depends on repetition – both of the tune and the lyrics. Too much repetition and it is just boring; too little, and it can lack structure. This article looks at different aspects of repetition in song lyrics.
Continue reading →