{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:08:40Z","timestamp":1750306120517,"version":"3.41.0"},"reference-count":62,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2017,6,23]],"date-time":"2017-06-23T00:00:00Z","timestamp":1498176000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"FWF Austrian Science Fund research project \u201cNavigability of Decentralized Information Networks.\u201d"},{"name":"DFG German Science Fund research project \u201cPoSTs II\u201d"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Web"],"published-print":{"date-parts":[[2017,8,31]]},"abstract":"<jats:p>\n            When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful, for example, for improving underlying network structures, predicting user clicks, or enhancing recommendations. In this work, we present a method called\n            <jats:italic>HypTrails<\/jats:italic>\n            for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our method utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to calculate the evidence of the data under them. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method, and to compare the relative plausibility of hypotheses, we employ Bayes factors. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including Web site navigation, business reviews, and online music played. Our work expands the repertoire of methods available for studying human trails.\n          <\/jats:p>","DOI":"10.1145\/3054950","type":"journal-article","created":{"date-parts":[[2017,6,26]],"date-time":"2017-06-26T12:13:22Z","timestamp":1498479202000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["A Bayesian Method for Comparing Hypotheses About Human Trails"],"prefix":"10.1145","volume":"11","author":[{"given":"Philipp","family":"Singer","sequence":"first","affiliation":[{"name":"GESIS - Leibniz Institute for the Social Sciences and University of Koblenz-Landau, Koblenz, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Denis","family":"Helic","sequence":"additional","affiliation":[{"name":"Technical University of Graz, Graz, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"Hotho","sequence":"additional","affiliation":[{"name":"University of W\u00fcrzburg, W\u00fcrzburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Markus","family":"Strohmaier","sequence":"additional","affiliation":[{"name":"GESIS - Leibniz Institute for the Social Sciences and University of Koblenz-Landau, Koblenz, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,6,23]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/375551.375608"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2660460.2660469"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/11805816_22"},{"key":"e_1_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Albert-L\u00e1szl\u00f3 Barab\u00e1si and R\u00e9ka Albert. 1999. Emergence of scaling in random networks. Science 286 5439 509--512.  Albert-L\u00e1szl\u00f3 Barab\u00e1si and R\u00e9ka Albert. 1999. Emergence of scaling in random networks. Science 286 5439 509--512.","DOI":"10.1126\/science.286.5439.509"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2809563.2809608"},{"key":"e_1_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Martin Becker Hauke Mewes Andreas Hotho Dimitar Dimitrov Florian Lemmerich and Markus Strohmaier. 2016. SparkTrails: A MapReduce Implementation of HypTrails for Comparing Hypotheses About Human Trails. Available at http:\/\/dmir.org\/sparktrails\/.  Martin Becker Hauke Mewes Andreas Hotho Dimitar Dimitrov Florian Lemmerich and Markus Strohmaier. 2016. SparkTrails: A MapReduce Implementation of HypTrails for Comparing Hypotheses About Human Trails. 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