The Specific Facet Search Strategy in ERIC/FirstSearch

This week I performed a specific facet search in the ERIC/FirstSearch database. With this strategy, you find your most specific facet first. Then, you combine facets, one at a time, until you reach your facet that produces the most results. Search results should be checked each time before adding another facet to make sure that the records retrieved make sense.

The topic of interest and naive question are the same as before.

Topic of Interest: Nonuser studies

Naïve Question: What are some of the characteristics of nonuser groups identified by public libraries?

The following table reflects the thesaurus terms gathered from ERIC/FirstSearch.

There were no thesaurus terms found for the first facet of nonuser groups, so I performed a keyword search here.

I then tried each of the following search strings using each facet individually to determine which facet is the most unique.

• SS1 keyword field search: nonuser* OR non-user*

RESULT: 442 records

• SS2 subject field search: public libraries

RESULT: 7,361 records

• SS3 subject field search: library research

RESULT: 6,552 records

SS1 is the most specific facet. I started with that and then added SS3 which yields the second smallest amount of results to get:

• SS4: (nonuser* [in keyword] OR non-user* [in keyword]) AND library research [in subject]

RESULT: 35 records

A final search was done using all three facets to see if anything can be found with the public libraries aspect added.

• SS5: (nonuser* [in keyword] OR non-user* [in keyword]) AND library research [in subject] AND public libraries [in subject]
  

Final result is 12 records.

Citation: Gallup Organization, Inc. (1975). The role of libraries in America. Princeton, NJ: Author.

This is a wonderful technique to find out which facet produces the least amount of results. Also, I was not expecting to see my results get limited so drastically once search statements started being combined because the facet with the most results is used last. However, any additional AND statement can bring the number of results down by any amount.

Successive Fraction Search Strategy with Library Literature

In class, we are all finding out how much practice it takes to perfect searching for material effectively. We are learning different types of search techniques to be able to pull information that we need from databases. This week I gave the successive fraction search strategy a try using the Library Literature database. In this technique, you are supposed to search the facet that gives you the most results first and then add additional facets one at a time, ending with the most unique facet. Here is an account of my search strategy experience.

Naive Question: What are some of the characteristics of nonuser groups identified by public libraries?

Focus groups could bring in the specific aspect of why certain groups of people are not using the library, so this was added as a facet as well.

I then tried each of the following search strings using each facet individually to determine which gives the largest retrieval.

• SS1: public libraries/non-users [in subject] OR non-user* [in Smart Search] OR nonuser* [in Smart Search]
  

The term non-users is being searched using a Smart Search as part of this facet in an attempt to get as many results as possible. The search is conducted with and without the dash to cover all spelling scenarios. Smart Search will try to find a term in the actual document or bibliographic record as well as the subject, author, title, journal name, and abstract fields.

RESULT: 25 records

• SS2 subject field search: public libraries

RESULT: 19,295 records

• SS3 subject field search: focus groups

RESULT: 97 records

SS2 yields the most results. I started with that and then added SS3 which yields the second largest amount of results to get:

• SS4 subject field search: public libraries AND focus groups

RESULT: 8 records – Two facets narrow the results down considerably!

I did another search using all three facets to see if anything can be found with the nonuser aspect added in.

• SS5 search: public libraries [in subject] AND focus groups [in subject] AND (public libraries/non-users [in subject] OR non-user* [in Smart Search] OR nonuser* [in Smart Search])

RESULT: 1 record

Citation: Tyerman, K. (1996). Getting things in focus: the use of focus groups in Brent Libraries. Library Management, 17(2), 36-9.

This is too narrow. Out of curiosity, I searched to see what I would get without the focus group facet, which brought down 19,295 records to 8 records. This facet may be what is limiting my search. This gives the following search statement.

• SS6 search: public libraries [in subject] AND (public libraries/non-users [in subject] OR non-user* [in Smart Search] OR nonuser* [in Smart Search])

RESULT: 16 records

As I guessed, the focus group facet was too limiting! I was able to get more of what I needed without even using this facet.

Citation: Harris, K. (2001). Who are they? In search of the elusive non-user. Colorado Libraries, 27(4), 16-18.

This is a wonderful technique for finding out how much of a topic is covered in a database or if it is covered at all. Sometimes combining the two broadest terms can be more limiting! Therefore, trying to combine the facets in a different way after analyzing the search results can prove helpful.