The methods used for biological sequence alignment have also found applications in other fields, most notably in [[natural language processing]] and in [[Sequence analysis in social sciences|social sciences]], where the [[Needleman-Wunsch algorithm]] is usually referred to as [[Optimal matching]].<ref>{{cite journal|author1=Abbott A. |author2=Tsay A. | year=2000 | title=Sequence Analysis and Optimal Matching Methods in Sociology, Review and Prospect | journal=Sociological Methods and Research | volume=29|issue=1 | pages=3–33 | doi=10.1177/0049124100029001001|s2cid=121097811 }}</ref> Techniques that generate the set of elements from which words will be selected in [[natural language generation|natural-language generation]] algorithms have borrowed multiple sequence alignment techniques from bioinformatics to produce linguistic versions of [[automated theorem proving|computer-generated mathematical proofs]].<ref name=Barzilay>{{cite book|author1=Barzilay R |author2=Lee L. |title=Proceedings of the ACL-02 conference on Empirical methods in natural language processing - EMNLP '02 |chapter=Bootstrapping lexical choice via multiple-sequence alignment |year=2002 | pages=164–171 | chapter-url=httphttps://www.cs.cornell.edu/home/llee/papers/gen-msa.pdf| volume=10| doi=10.3115/1118693.1118715|arxiv=cs/0205065|bibcode=2002cs........5065B |s2cid=7521453 }}</ref> In the field of historical and comparative [[linguistics]], sequence alignment has been used to partially automate the [[comparative method (linguistics)|comparative method]] by which linguists traditionally reconstruct languages.<ref>{{cite thesis |author=Kondrak, Grzegorz |title=Algorithms for Language Reconstruction |publisher=University of Toronto |year=2002 |url=http://www.cs.ualberta.ca/~kondrak/papers/thesis.pdf |access-date=2007-01-21 |archive-url=https://web.archive.org/web/20081217043010/http://www.cs.ualberta.ca/~kondrak/papers/thesis.pdf |archive-date=17 December 2008 |url-status=dead }}</ref> Business and marketing research has also applied multiple sequence alignment techniques in analyzing series of purchases over time.<ref name=prinzie>{{cite journal|author1=Prinzie A. |author2=D. Van den Poel |year=2006 | url=http://econpapers.repec.org/paper/rugrugwps/05_2F292.htm | title=Incorporating sequential information into traditional classification models by using an element/position-sensitive SAM | journal=Decision Support Systems | volume=42 | issue=2| pages= 508–526 | doi=10.1016/j.dss.2005.02.004| url-access=subscription }} See also Prinzie and Van den Poel's paper {{cite journal | url=http://econpapers.repec.org/paper/rugrugwps/07_2F442.htm | title=Predicting home-appliance acquisition sequences: Markov/Markov for Discrimination and survival analysis for modeling sequential information in NPTB models | year=2007 | journal=Decision Support Systems | volume=44 | issue=1 | pages= 28–45 | doi=10.1016/j.dss.2007.02.008 | author=Prinzie, A | last2=Vandenpoel | first2=D| url-access=subscription }}</ref>
