1006_the demographics of web search

8/7/2019 1006_The Demographics of Web Search

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SIGIR 2010


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Query Disambiguation

A query wagner

Forwomen the most clicked URL was composer

Formen the most clicked URL was paint sprayers An incomplete term hal

In general hal indsey (evangelist)

People living in areas with above average

education level is hal higdon (writerandrunner)


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How to solve ambiguities

Grouping users bydemographic features, such

as age orincome.

Models are learned forindividual users. Given enough data about individual users,

models indeed be proofedvery powerful.


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Contribution

Wedemonstrate how public information forZIPcodes can beused to annotate both web queries andURLs with demographic features.

We show that theuserpopulation of a large,commercial search engine is representative of thewhole US population.

Weuncoverdifferences in search behavioracrossdemographic segments.

We show that using demographic information has apotential to improve state-of-the-art web searchresults.


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Query Log Preprocessing

Fourth, only web searches originating from the US-version of the search engine

pertaining to users with a valid ZIP code wereused

Fifth, queries without clicks on URLs werediscarded when multiple URLs where clicked forthe same query, multiple such

pairs were generated.

Sixth, queries were cast to lowercase but no stemming wasapplied and all special characters (such as apostrophes) werekept.

Seventh, immediate, repeatedduplicates of (query, URL) pairsby a singleuserwere conflated to a single instance.

we still kept repeated (query, URL) pairs fora singleuseras long asthere were otherpairs in between. (q,u1)

(q,u1)

(q,u1)

(q,u1)

(q,u2)

(q,u1)


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Basic statistics


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Demographic Feature Extraction

percapita income [P-c income k$]

bachelor's degree orhigher[BA degree %]

individuals below poverty level [below poverty %], race: white [white %], African American [African

American %], Asian [Asian %]

speaks a language otherthan English at home [non-English %].


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Pairs (input, target) were then labeled with

demographic information

directly from theuser's profile (birth yearandgender)

from using demographic information pertaining to

ZIP codes


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The labels applied to each (input, target) pairwerediscretized

Forall demographic features weused quintiles: thepercentile intervals [0%; 20%], (20%; 40%], ..., (80%;100].

E.g., a ZIP code with no more than 12.8% of itspopulation 25 years and overholding a bachelor'sdegree would be placed in the lowest quintile forthe

corresponding feature the ZIP where weused only the two leading digits

giving a total of 99 buckets,


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Data Quality

Users provided false profile information,

sometimes deliberately.

Solution derived the ZIP code by mapping theuser's IP


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METHODOLOGY

LetX, YandDberandom variables

corresponding to the input, target and

demographic information respectively.

Similarly, letx,y anddbe actual instances of

values of theserandom variables.

argmaxy

P(y |x, d) argmaxy

P(y |x)


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Table lists the fourmost

discriminating queries for

different demographicgroups

Query of Max P(D|Q)

Queries areranked by theaverage featurevalue

Olderpeople tend to be

more likely to use URLs as

web queries


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Finding

Queries predominantly issued byyoung userstend to berelated to chat rooms, music andsocial networking sites.

Queries which are issuedexclusively bymaleusers in oursample arerelated to sports, orcomputerhard and software.

Queries from areas where a language otherthan English is often spoken at home, turn outto be written in Spanish.


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People with a universitydegree

behavior

Numbers are computed overroughly 95.8M

Thesedifferences, though small, are statisticallysignificant at a confidence level well below 0.001,

using a t-test


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Conditional entropy

A queries q where a demographic group dhas anunusually high orlow conditional clickentropyH(U|q, d)

A high clickentropy can bedue to a numberofreasons. It can be that the presented web results forthat query are

poorand people have to try many pages

but it can also be seen an expression of high interest on apotentially multi-faceted topic


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Application Results

The input has a support of at least 100 users forsomecombination (x,d), as well as at least another400 users forothervalues ofd.

The baseline system ranks targets according to P(y|x).

Oursystem ranks them byP(y|x, d).

The last column shows therelative gain.


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Conclusion

This is the first study that analyzes the websearch behaviorofdifferent demographicgroups formillions of US web users.

The simple but important observation thatmade this possible was the linkage of censusinformation forZIP codes.

Formost parts, the population of search engineusers appears to be a very good approximationof the US population.

1006_the demographics of web search

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