{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T01:49:20Z","timestamp":1772070560995,"version":"3.50.1"},"reference-count":56,"publisher":"Emerald","issue":"6","license":[{"start":{"date-parts":[[2020,6,26]],"date-time":"2020-06-26T00:00:00Z","timestamp":1593129600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JEIM"],"published-print":{"date-parts":[[2020,6,26]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to explore to which extent the quality of social media short text without extensions can be investigated and what are the predictors, if any, of such short text that lead to trust its content.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>The paper applies a trust model to classify data collections based on metadata into four classes: Very Trusted, Trusted, Untrusted and Very Untrusted. These data are collected from the online communities, Genius and Stack Overflow. In order to evaluate short texts in terms of its trust levels, the authors have conducted two investigations: (1) A natural language processing (NLP) approach to extract relevant features (i.e. Part-of-Speech and various readability indexes). The authors report relatively good performance of the NLP study. (2) A machine learning technique in more precise, a random forest (RF) classifierusing bag-of-words model (BoW).<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The investigation of the RF classifier using BoW shows promising intermediate results (on average 62% accuracy of both online communities) in short-text quality identification that leads to trust.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title><jats:p>As social media becomes an increasingly new and attractive source of information, which is mostly provided in the form of short texts, businesses (e.g. in search engines for smart data) can filter content without having to apply complex approaches and continue to deal with information that is considered more trustworthy.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>Short-text classifications with regard to a criterion (e.g. quality, readability) are usually extended by an external source or its metadata. This enhancement either changes the original text if it is an additional text from an external source, or it requires text metadata that is not always available. To this end, the originality of this study faces the challenge of investigating the quality of short text (i.e. social media text) without having to extend or modify it using external sources. This modification alters the text and distorts the results of the investigation.<\/jats:p><\/jats:sec>","DOI":"10.1108\/jeim-06-2019-0156","type":"journal-article","created":{"date-parts":[[2020,6,26]],"date-time":"2020-06-26T05:15:28Z","timestamp":1593148528000},"page":"1443-1466","source":"Crossref","is-referenced-by-count":18,"title":["Exploring the impact of short-text complexity and structure on its quality in social media"],"prefix":"10.1108","volume":"33","author":[{"given":"Jamal","family":"Al Qundus","sequence":"first","affiliation":[]},{"given":"Adrian","family":"Paschke","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2714-4958","authenticated-orcid":false,"given":"Shivam","family":"Gupta","sequence":"additional","affiliation":[]},{"given":"Ahmad M.","family":"Alzouby","sequence":"additional","affiliation":[]},{"given":"Malik","family":"Yousef","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020120705095897100_ref001","first-page":"3","article-title":"Generating trust in collaborative annotation environments","year":"2016"},{"key":"key2020120705095897100_ref002","volume-title":"Technical Analysis of the Social Media Platform Genius","year":"2018"},{"key":"key2020120705095897100_ref005","first-page":"278","article-title":"Investigating the effect of attributes on user trust in social media","year":"2018"},{"key":"key2020120705095897100_ref004","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ijinfomgt.2019.01.012","article-title":"Calculating trust in domain analysis: theoretical trust model","volume":"48","year":"2019","journal-title":"International Journal of Information Management"},{"key":"key2020120705095897100_ref003","article-title":"AI supported topic modeling using KNIME-workflows","year":"2020"},{"key":"key2020120705095897100_ref006","first-page":"2","volume-title":"How to Evaluate and Create Information Quality on the Web","year":"1999"},{"issue":"2","key":"key2020120705095897100_ref007","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1108\/IJWIS-12-2017-0083","article-title":"Review of short-text classification","volume":"15","year":"2019","journal-title":"International Journal of Web Information Systems"},{"key":"key2020120705095897100_ref008","first-page":"43","article-title":"A \u2018quick and dirty\u2019 website data quality indicator","year":"2008"},{"key":"key2020120705095897100_ref009","article-title":"How bad do you spell?: the lexical quality of social media","year":"2011"},{"issue":"1","key":"key2020120705095897100_ref010","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1162\/coli.2008.34.1.1","article-title":"Modeling local coherence: an entity-based approach","volume":"34","year":"2008","journal-title":"Computational Linguistics"},{"issue":"1","key":"key2020120705095897100_ref011","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1145\/1656274.1656280","article-title":"KNIME-the konstanz information miner: version 2.0 and beyond","volume":"11","year":"2009","journal-title":"AcM SIGKDD Explorations Newsletter"},{"issue":"2","key":"key2020120705095897100_ref012","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1108\/17410390510579927","article-title":"The relationship between system usage and user satisfaction: a meta-analysis","volume":"18","year":"2005","journal-title":"Journal of Enterprise Information Management"},{"issue":"4","key":"key2020120705095897100_ref013","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/j.ijinfomgt.2010.01.004","article-title":"Relationship quality, community promotion and brand loyalty in virtual communities: evidence from free software communities","volume":"30","year":"2010","journal-title":"International Journal of Information Management"},{"key":"key2020120705095897100_ref014","first-page":"67","article-title":"Linguistic features of English textese and digitalk of Iranian EFL students","volume":"8","year":"2017","journal-title":"Research in Applied Linguistics"},{"issue":"3","key":"key2020120705095897100_ref015","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1037\/h0057532","article-title":"A new readability yardstick","volume":"32","year":"1948","journal-title":"Journal of Applied Psychology"},{"issue":"3","key":"key2020120705095897100_ref016","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1108\/JEIM-07-2017-0101","article-title":"Understanding social media advertising effect on consumers' responses: an empirical investigation of tourism advertising on facebook","volume":"31","year":"2018","journal-title":"Journal of Enterprise Information Management"},{"key":"key2020120705095897100_ref017","first-page":"83","article-title":"Language of vandalism: improving Wikipedia vandalism detection via stylometric analysis","year":"2011"},{"key":"key2020120705095897100_ref018","article-title":"Detecting text similarity over short passages: exploring linguistic feature combinations via machine learning","year":"1999"},{"issue":"1","key":"key2020120705095897100_ref019","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1108\/JEIM-02-2018-0031","article-title":"Identifying customer knowledge on social media through data analytics","volume":"32","year":"2019","journal-title":"Journal of Enterprise Information Management"},{"key":"key2020120705095897100_ref020","first-page":"460","article-title":"Combining lexical and grammatical features to improve readability measures for first and second language texts","year":"2007"},{"issue":"1","key":"key2020120705095897100_ref021","first-page":"6","article-title":"Design science in information systems research","volume":"28","year":"2008","journal-title":"Management Information Systems Quarterly"},{"key":"key2020120705095897100_ref022","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1016\/j.patcog.2017.09.045","article-title":"Concept decompositions for short text clustering by identifying word communities","volume":"76","year":"2018","journal-title":"Pattern Recognition"},{"key":"key2020120705095897100_ref023","article-title":"Short text topic modeling techniques, applications, and performance: a survey","year":"2019"},{"issue":"2","key":"key2020120705095897100_ref024","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1108\/JEIM-11-2014-0109","article-title":"Text mining stackoverflow: an insight into challenges and subject-related difficulties faced by computer science learners","volume":"29","year":"2016","journal-title":"Journal of Enterprise Information Management"},{"key":"key2020120705095897100_ref025","first-page":"256","article-title":"Web document classification by keywords using random forests","year":"2010"},{"issue":"3","key":"key2020120705095897100_ref026","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1080\/08824090109384803","article-title":"Dichotomous and continuous views of deception: a reexamination of deception ratings in information manipulation theory","volume":"18","year":"2001","journal-title":"Communication Research Reports"},{"issue":"5","key":"key2020120705095897100_ref027","first-page":"996","article-title":"Read, watch, listen, and summarize: multi-modal summarization for asynchronous text, image, audio and video","volume":"31","year":"2018","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"2","key":"key2020120705095897100_ref028","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1108\/JEIM-10-2015-0094","article-title":"Enabling internet banking adoption: an empirical examination with an augmented technology acceptance model (TAM)","volume":"30","year":"2017","journal-title":"Journal of Enterprise Information Management"},{"issue":"4","key":"key2020120705095897100_ref029","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/0167-9236(94)00041-2","article-title":"Design and natural science research on information technology","volume":"15","year":"1995","journal-title":"Decision Support Systems"},{"issue":"1","key":"key2020120705095897100_ref030","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/03637759209376245","article-title":"Information manipulation theory","volume":"59","year":"1992","journal-title":"Communications Monographs"},{"key":"key2020120705095897100_ref031","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.jbi.2017.03.014","article-title":"NegAIT: a new parser for medical text simplification using morphological, sentential and double negation","volume":"69","year":"2017","journal-title":"Journal of Biomedical Informatics"},{"issue":"5","key":"key2020120705095897100_ref032","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1108\/17410390910993527","article-title":"Trust or distrust in the web-mediated information environment (W-MIE) A perspective of online muslim users","volume":"22","year":"2009","journal-title":"Journal of Enterprise Information Management"},{"issue":"2","key":"key2020120705095897100_ref033","first-page":"430","article-title":"Predicting completion risk in PPP projects using big data analytics","volume":"67","year":"2018","journal-title":"IEEE Transactions on Engineering Management"},{"key":"key2020120705095897100_ref034","first-page":"186","article-title":"Revisiting readability: a unified framework for predicting text quality","year":"2008"},{"key":"key2020120705095897100_ref035","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.ijinfomgt.2018.02.004","article-title":"Didn't roger that: social media message complexity and situational awareness of emergency responders","volume":"40","year":"2018","journal-title":"International Journal of Information Management"},{"key":"key2020120705095897100_ref036","first-page":"541","article-title":"Improving low quality Stack Overflow post detection","year":"2014"},{"key":"key2020120705095897100_ref037","first-page":"663","article-title":"Automatic vandalism detection in Wikipedia","year":"2008"},{"key":"key2020120705095897100_ref038","first-page":"1","article-title":"Artifact evaluation in information systems design-science research-a holistic view","volume":"23","year":"2014","journal-title":"PACIS"},{"issue":"8","key":"key2020120705095897100_ref039","doi-asserted-by":"crossref","first-page":"978","DOI":"10.1016\/j.im.2016.04.005","article-title":"Social emotion classification of short text via topic-level maximum entropy model","volume":"53","year":"2016","journal-title":"Information and Management"},{"key":"key2020120705095897100_ref040","article-title":"Exploring the feasibility of automatically rating online article quality","year":"2007"},{"issue":"1","key":"key2020120705095897100_ref041","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1108\/JEIM-06-2015-0047","article-title":"Social media content and product co-creation: an emerging paradigm","volume":"29","year":"2016","journal-title":"Journal of Enterprise Information Management"},{"issue":"1","key":"key2020120705095897100_ref042","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1108\/JEIM-04-2012-0011","article-title":"Technology acceptance model (TAM) and social media usage: an empirical study on facebook","volume":"27","year":"2014","journal-title":"Journal of Enterprise Information Management"},{"key":"key2020120705095897100_ref043","first-page":"279","article-title":"Understanding judgment of information quality and cognitive authority in the WWW","year":"1998"},{"key":"key2020120705095897100_ref044","first-page":"523","article-title":"Reading level assessment using support vector machines and statistical language models","year":"2005"},{"key":"key2020120705095897100_ref045","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1214\/07-SS016","article-title":"Text data mining: theory and methods","volume":"2","year":"2008","journal-title":"Statistics Surveys"},{"key":"key2020120705095897100_ref046","first-page":"841","article-title":"Short text classification in twitter to improve information filtering","year":"2010"},{"issue":"2005","key":"key2020120705095897100_ref047","first-page":"442","article-title":"Assessing information quality of a community-based encyclopedia","volume":"5","year":"2005","journal-title":"ICIQ"},{"issue":"4","key":"key2020120705095897100_ref048","first-page":"37","article-title":"Modeling design processes","volume":"11","year":"1990","journal-title":"AI Mag"},{"key":"key2020120705095897100_ref049","first-page":"987","article-title":"Are cohesive features relevant for text readability evaluation?","year":"2016"},{"issue":"7","key":"key2020120705095897100_ref050","first-page":"809","article-title":"Improving accuracy of named entity recognition on social media","volume":"5","year":"2017","journal-title":"IJSEAT"},{"key":"key2020120705095897100_ref051","first-page":"1146","article-title":"Got you!: automatic vandalism detection in Wikipedia with web-based shallow syntactic-semantic modeling","year":"2010"},{"issue":"6","key":"key2020120705095897100_ref052","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1108\/17410390410566724","article-title":"SiteQual: an integrated measure of web site quality","volume":"17","year":"2004","journal-title":"Journal of Enterprise Information Management"},{"issue":"8","key":"key2020120705095897100_ref053","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1016\/j.future.2011.02.007","article-title":"Trust in collaborative web applications","volume":"28","year":"2012","journal-title":"Future Generation Computer Systems"},{"issue":"1","key":"key2020120705095897100_ref054","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0169-7439(00)00122-2","article-title":"Monte Carlo cross validation","volume":"56","year":"2001","journal-title":"Chemometrics and Intelligent Laboratory Systems"},{"key":"key2020120705095897100_ref055","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.procs.2013.09.083","article-title":"Combining lexical and semantic features for short text classification","volume":"22","year":"2013","journal-title":"Procedia Computer Science"},{"issue":"3","key":"key2020120705095897100_ref056","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1177\/1046878111422560","article-title":"Natural language processing in game studies research: an overview","volume":"43","year":"2012","journal-title":"Simulation and Gaming"}],"container-title":["Journal of Enterprise Information Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/JEIM-06-2019-0156\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/JEIM-06-2019-0156\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T22:31:32Z","timestamp":1753396292000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/jeim\/article\/33\/6\/1443-1466\/434302"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,26]]},"references-count":56,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2020,6,26]]}},"alternative-id":["10.1108\/JEIM-06-2019-0156"],"URL":"https:\/\/doi.org\/10.1108\/jeim-06-2019-0156","relation":{},"ISSN":["1741-0398"],"issn-type":[{"value":"1741-0398","type":"print"}],"subject":[],"published":{"date-parts":[[2020,6,26]]}}}