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Literature Reviews: Identify keywords

Identifying keywords

It is important to find all the relevant keywords for the topic to ensure the search is comprehensive by identifying:

  • different spellings, tenses and word variants of keywords
  • synonyms
  • related concepts
  • names of people or authors associated with these ideas

There are many  ways to locate these terms, including

  • recommended readings, textbooks and other review articles that provide an overview of the field of  research
  • dictionaries, thesauri, handbooks and encyclopedias that provide definitions and general information about topics.
  • database thesauri or subject headings that tell you which terms are used in the databases and professional literature.
  • text mining tools that allow you to analyse large amounts of text or information and identify commonly used terms in the field.

The process of searching will also help identify more terms that you should be adding to your list.

Comprehesive vs precise

There needs to be a balance in searching between making the search comprehensive enough to encompass everything on the topic and precise enough to only capture those results that are specifically relevant.

Both approaches have advantages and disadvantages

Type of Search
Comprehensive
Precise
Advantages
Broad search finds everything on topic Specific to topic so results are more relevant
 

Lessens chance of missing relevant papers

Easier to discard irrelevant results

Disadvantages
Too much information to process easily Not enough results
 
Many irrelevant results to discard Many relevant papers missed as topic too narrow

Increasing the comprehensiveness (or sensitivity) of a search will reduce its precision and will retrieve more non-relevant articles.

Using text mining to identify keywords

Text mining will help identify how often terms come up in the literature and help identify other related terms and subject headings that have not been considered or thought of as being useful.

Text mining is a process used to look at large amounts of text and find relationships in the results by using computer programs designed to extract and analyse this data. 

It is used to categorise information and identify trends and patterns which can be done across large documents or multiple sources (or both).

Methods

1. Mining for terms
Use these tools to find alternate search terms that are related by identifying how often keywords appear and which other terms appear with them by number of occurrences.

2. Mine within the text
Locate terms within blocks of text (e.g. an article) to find word patterns and frequency. More frequent words are more likely to be relevant to the topic.

3. Use visualising tools
These tools create word clouds related to search terms

These are just some of the tools available for mining text that are available on the web. There is also both commercial and free software that can be downloaded and installed. The web pages linked below have lists of yet more tools.

Further reading:

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