{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T16:13:38Z","timestamp":1761581618611,"version":"3.41.0"},"reference-count":22,"publisher":"Association for Computing Machinery (ACM)","issue":"5","license":[{"start":{"date-parts":[[2017,10,25]],"date-time":"2017-10-25T00:00:00Z","timestamp":1508889600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGCOMM Comput. Commun. Rev."],"published-print":{"date-parts":[[2017,10,25]]},"abstract":"<jats:p>Clearly, no one likes webpages with poor quality of experience (QoE). Being perceived as slow or fast is a key element in the overall perceived QoE of web applications. While extensive effort has been put into optimizing web applications (both in industry and academia), not a lot of work exists in characterizing what aspects of webpage loading process truly influence human end-user's perception of the \\emph{Speed} of a page. In this paper we present \\emph{SpeedPerception}, a large-scale web performance crowdsourcing framework focused on understanding the perceived loading performance of above-the-fold (ATF) webpage content. Our end goal is to create free open-source benchmarking datasets to advance the systematic analysis of how humans perceive webpage loading process.<\/jats:p>\n          <jats:p>In Phase-1 of our \\emph{SpeedPerception} study using Internet Retailer Top 500 (IR 500) websites, we found that commonly used navigation metrics such as \\emph{onLoad} and \\emph{Time To First Byte (TTFB)} fail (less than 60\\% match) to represent majority human perception when comparing the speed of two webpages. We present a simple 3-variable-based machine learning model that explains the majority end-user choices better (with $87 \\pm 2\\%$ accuracy). In addition, our results suggest that the time needed by end-users to evaluate relative perceived speed of webpage is far less than the time of its \\emph{visualComplete} event.<\/jats:p>","DOI":"10.1145\/3155055.3155062","type":"journal-article","created":{"date-parts":[[2017,10,26]],"date-time":"2017-10-26T14:19:33Z","timestamp":1509027573000},"page":"42-47","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Perceived Performance of Top Retail Webpages In the Wild"],"prefix":"10.1145","volume":"47","author":[{"family":"Qingzhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prasenjit","family":"Dey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Parvez","family":"Ahammad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,10,25]]},"reference":[{"key":"e_1_2_1_1_2","unstructured":"Google Chrome Lighthouse Project https:\/\/github.com\/googlechrome\/lighthouse.  Google Chrome Lighthouse Project https:\/\/github.com\/googlechrome\/lighthouse."},{"key":"e_1_2_1_2_2","unstructured":"SpeedIndex https:\/\/sites.google.com\/a\/webpagetest.org\/docs\/using-webpagetest\/metrics\/speed-index.  SpeedIndex https:\/\/sites.google.com\/a\/webpagetest.org\/docs\/using-webpagetest\/metrics\/speed-index."},{"key":"e_1_2_1_3_2","unstructured":"SpeedPerception Benchmark and Results https:\/\/github.com\/pahammad\/speedperception.  SpeedPerception Benchmark and Results https:\/\/github.com\/pahammad\/speedperception."},{"key":"e_1_2_1_4_2","unstructured":"SpeedPerception Experimental UI http:\/\/speedperception.com.  SpeedPerception Experimental UI http:\/\/speedperception.com."},{"key":"e_1_2_1_5_2","unstructured":"The Very Real Performance Impact on Revenue http:\/\/blog.catchpoint.com\/2017\/01\/06\/performance-impact-revenue-real\/.  The Very Real Performance Impact on Revenue http:\/\/blog.catchpoint.com\/2017\/01\/06\/performance-impact-revenue-real\/."},{"key":"e_1_2_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2015.7177516"},{"key":"e_1_2_1_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/2639108.2639137"},{"key":"e_1_2_1_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3027947.3027949"},{"key":"e_1_2_1_9_2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_2_1_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/2068816.2068846"},{"key":"e_1_2_1_11_2","unstructured":"E. Carbery. Website Performance: The Need for Speed http:\/\/www.6smarketing.com\/blog\/website-performance-the-need-for-speed\/.  E. Carbery. Website Performance: The Need for Speed http:\/\/www.6smarketing.com\/blog\/website-performance-the-need-for-speed\/."},{"key":"e_1_2_1_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1389-1286(02)00184-6"},{"key":"e_1_2_1_13_2","unstructured":"H. Cram\u00e9r. Mathematical Methods of Statistics volume 9. Princeton university press 2016.  H. Cram\u00e9r. Mathematical Methods of Statistics volume 9. Princeton university press 2016."},{"key":"e_1_2_1_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2012.6363769"},{"key":"e_1_2_1_15_2","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1013203451"},{"key":"e_1_2_1_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2013.2291663"},{"volume-title":"The Practical Handbook of Internet Computing","year":"2005","author":"Iyengar A.","key":"e_1_2_1_17_2"},{"key":"e_1_2_1_18_2","first-page":"545","article-title":"Improving user perceived page load times using Gaze","volume":"17","author":"Kelton C.","journal-title":"USENIX NSDI"},{"volume-title":"USENIX NSDI 2016","year":"2016","author":"Netravali R.","key":"e_1_2_1_19_2"},{"key":"e_1_2_1_20_2","doi-asserted-by":"publisher","DOI":"10.1145\/2999572.2999590"},{"volume-title":"USENIX NSDI","year":"2016","author":"Wang X. S.","key":"e_1_2_1_21_2"},{"key":"e_1_2_1_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"}],"container-title":["ACM SIGCOMM Computer Communication Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3155055.3155062","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3155055.3155062","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:26:40Z","timestamp":1750213600000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3155055.3155062"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,25]]},"references-count":22,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2017,10,25]]}},"alternative-id":["10.1145\/3155055.3155062"],"URL":"https:\/\/doi.org\/10.1145\/3155055.3155062","relation":{},"ISSN":["0146-4833"],"issn-type":[{"type":"print","value":"0146-4833"}],"subject":[],"published":{"date-parts":[[2017,10,25]]},"assertion":[{"value":"2017-10-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}