BEGIN:VCALENDAR VERSION:2.0 X-WR-CALNAME:EventsCalendar PRODID:-//hacksw/handcal//NONSGML v1.0//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York LAST-MODIFIED:20240422T053451Z TZURL:https://www.tzurl.org/zoneinfo-outlook/America/New_York X-LIC-LOCATION:America/New_York BEGIN:DAYLIGHT TZNAME:EDT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 DTSTART:19700308T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZNAME:EST TZOFFSETFROM:-0400 TZOFFSETTO:-0500 DTSTART:19701101T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT CATEGORIES:College of Arts and Sciences,College of Engineering,Graduate Stu dies,Lectures and Seminars,Thesis/Dissertations DESCRIPTION:Advisor: Dr. José Domingo Mora - Associate Professor & Chairpe rson, Management & Marketing Committee Members:  Dr. Donghui Yan - Data S cience Co-Director & Department of MathematicsDr. Yuchou Chang - Departmen t of Computer & Information Science Date: Wednesday, August 19th, 2026Time : 11:00AM – 12:00 PM (Eastern Time)Location: Zoom (please contact: tpasu marthi@umassd.edu or josedomingo.mora@umassd.edu for Zoom information) Com mittee Members:  Dr. Donghui Yan - Data Science Co-Director & Department of Mathematics     Dr. Yuchou Chang - Department of Computer & Informat ion Science Abstract: Online reviews are consumed in volume and evaluated rapidly, making the linguistic properties of their earliest words conseque ntial. Mora and Izadi (2024) demonstrated that the grammatical and syntact ic composition of a review's opening carries diagnostic information about the register of the full text, and that this register co-occurs with perce ived helpfulness. This thesis operationalizes and extends that account thr ough a reproducible seven-stage computational pipeline applied to 9,999 Am azon reviews drawn equally from the Books and Electronics domains. Review openings were parsed for dependency and constituency structure, abstracted into canonical syntactic templates, embedded as sentence vectors, and clu stered using k-means. An eight-class taxonomy of opening strategies was se lected on the basis of clustering evaluation metrics and stability across random initializations (mean adjusted Rand index = 0.99). The taxonomy was validated against manual annotation and tested for association with helpf ulness using nested negative binomial regression and for cross-domain gene ralizability using chi-square and Kruskal–Wallis tests. Opening class wa s significantly associated with helpfulness after controlling for review l ength, star rating, domain, and reviewer activity, and this association va ried by domain. Taxonomy composition was broadly stable across domains, co nfirming cross-domain generalizability. Validation further revealed that t he pipeline's embedding space captures semantic-functional organization ra ther than strictly syntactic structure, an empirical finding about how com putational methods represent register. The thesis contributes an automated , evaluated, and reproducible alternative to semi-manual register analysis . For further questions, please contact Professor José Domingo Mora at jo sedomingo.mora@umassd.edu.\nEvent page: /events/cms/ 20260819-syntactic-openings-in-online-reviews.php X-ALT-DESC;FMTTYPE=text/html:

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Advisor:
Dr. José Doming o Mora - Associate Professor & Chairperson\, Management & Marketing

\n< p>Committee Members: 
Dr. Donghui Yan - Data Science Co-Director & Department of Mathematics
Dr. Yuchou Chang - Department of Computer & Information Science

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Date: Wednesday\, August 19th\, 2026
Tim e: 11:00AM – 12:00 PM (Eastern Time)
Location: Zoom (please contact : tpasumarthi@umassd.edu or josedomingo.mora@umassd.edu for Zoom informati on)

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Committee Members: 
Dr. Donghui Yan - Data Science Co-D irector & Department of Mathematics     
Dr. Yuchou Chang - Depart ment of Computer & Information Science

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Abstract:

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Online re views are consumed in volume and evaluated rapidly\, making the linguistic properties of their earliest words consequential. Mora and Izadi (2024) d emonstrated that the grammatical and syntactic composition of a review's o pening carries diagnostic information about the register of the full text\ , and that this register co-occurs with perceived helpfulness. This thesis operationalizes and extends that account through a reproducible seven-sta ge computational pipeline applied to 9\,999 Amazon reviews drawn equally f rom the Books and Electronics domains. Review openings were parsed for dep endency and constituency structure\, abstracted into canonical syntactic t emplates\, embedded as sentence vectors\, and clustered using k-means. An eight-class taxonomy of opening strategies was selected on the basis of cl ustering evaluation metrics and stability across random initializations (m ean adjusted Rand index = 0.99). The taxonomy was validated against manual annotation and tested for association with helpfulness using nested negat ive binomial regression and for cross-domain generalizability using chi-sq uare and Kruskal–Wallis tests. Opening class was significantly associate d with helpfulness after controlling for review length\, star rating\, dom ain\, and reviewer activity\, and this association varied by domain. Taxon omy composition was broadly stable across domains\, confirming cross-domai n generalizability. Validation further revealed that the pipeline's embedd ing space captures semantic-functional organization rather than strictly s yntactic structure\, an empirical finding about how computational methods represent register. The thesis contributes an automated\, evaluated\, and reproducible alternative to semi-manual register analysis.

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For fur ther questions\, please contact Professor José Domingo Mora at josedomingo.mora@umassd.edu.

Event page: /events/cms/20260819 -syntactic-openings-in-online-reviews.php

DTSTAMP:20260807T204302 DTSTART;TZID=America/New_York:20260819T110000 DTEND;TZID=America/New_York:20260819T120000 LOCATION:Zoom - please contact: tpasumarthi@umassd.edu or josedomingo.mora@ umassd.edu for Zoom information SUMMARY;LANGUAGE=en-us:Syntactic Openings in Online Reviews: A Computationa l Pipeline for Cross-Domain Register Taxonomy and Helpfulness Analysis UID:761efa5000ef6e747decbf90f3aa06a1@www.umassd.edu END:VEVENT END:VCALENDAR