{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T16:20:07Z","timestamp":1759335607978,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031484230"},{"type":"electronic","value":"9783031484247"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-48424-7_15","type":"book-chapter","created":{"date-parts":[[2023,11,21]],"date-time":"2023-11-21T20:03:21Z","timestamp":1700597001000},"page":"195-211","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Detecting Changes in\u00a0Crowdsourced Social Media Images"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2719-4955","authenticated-orcid":false,"given":"Muhammad","family":"Umair","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1254-8092","authenticated-orcid":false,"given":"Athman","family":"Bouguettaya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8005-1534","authenticated-orcid":false,"given":"Abdallah","family":"Lakhdari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,20]]},"reference":[{"key":"15_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1007\/978-3-030-02925-8_13","volume-title":"Web Information Systems Engineering \u2013 WISE 2018","author":"T Aamir","year":"2018","unstructured":"Aamir, T., Dong, H., Bouguettaya, A.: Stance and credibility based trust in social-sensor cloud services. In: Hacid, H., Cellary, W., Wang, H., Paik, H.-Y., Zhou, R. (eds.) WISE 2018. LNCS, vol. 11234, pp. 178\u2013189. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-02925-8_13"},{"key":"15_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1007\/978-3-030-62005-9_36","volume-title":"Web Information Systems Engineering \u2013 WISE 2020","author":"T Aamir","year":"2020","unstructured":"Aamir, T., Dong, H., Bouguettaya, A.: Heuristics based mosaic of social-sensor services for scene reconstruction. In: Huang, Z., Beek, W., Wang, H., Zhou, R., Zhang, Y. (eds.) WISE 2020. LNCS, vol. 12342, pp. 503\u2013515. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-62005-9_36"},{"issue":"2","key":"15_CR3","doi-asserted-by":"publisher","first-page":"1059","DOI":"10.1109\/TSC.2020.2974741","volume":"15","author":"T Aamir","year":"2020","unstructured":"Aamir, T., Dong, H., Bouguettaya, A.: Social-sensor composition for tapestry scenes. IEEE Trans. Serv. Comput. 15(2), 1059\u20131073 (2020)","journal-title":"IEEE Trans. Serv. Comput."},{"key":"15_CR4","doi-asserted-by":"crossref","unstructured":"Aamir, T., et al.: Trust in social-sensor cloud service. In: 2018 IEEE International Conference on Web Services (ICWS), pp. 359\u2013362. IEEE (2018)","DOI":"10.1109\/ICWS.2018.00061"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"Ali, K., Dong, H., Bouguettaya, A., Erradi, A., Hadjidj, R.: Sentiment analysis as a service: a social media based sentiment analysis framework. In: 2017 IEEE International Conference on Web Services (ICWS), pp. 660\u2013667. IEEE (2017)","DOI":"10.1109\/ICWS.2017.79"},{"key":"15_CR6","doi-asserted-by":"crossref","unstructured":"Bharati, A., et al.: Beyond pixels: image provenance analysis leveraging metadata. In: 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1692\u20131702. IEEE (2019)","DOI":"10.1109\/WACV.2019.00185"},{"key":"15_CR7","doi-asserted-by":"crossref","unstructured":"Chae, J., et al.: Spatiotemporal social media analytics for abnormal event detection and examination using seasonal-trend decomposition. In: 2012 IEEE Conference on Visual Analytics Science and Technology (VAST), pp. 143\u2013152. IEEE (2012)","DOI":"10.1109\/VAST.2012.6400557"},{"key":"15_CR8","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.chb.2019.03.032","volume":"97","author":"J Colliander","year":"2019","unstructured":"Colliander, J.: \u201cthis is fake news\u2019\u2019: investigating the role of conformity to other users\u2019 views when commenting on and spreading disinformation in social media. Comput. Hum. Behav. 97, 202\u2013215 (2019)","journal-title":"Comput. Hum. Behav."},{"key":"15_CR9","unstructured":"Ganti, D.: A novel method for detecting misinformation in videos, utilizing reverse image search, semantic analysis, and sentiment comparison of metadata. Utilizing Reverse Image Search, Semantic Analysis, and Sentiment Comparison of Metadata (2022)"},{"issue":"11","key":"15_CR10","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.3758","volume":"16","author":"HM Griffis","year":"2014","unstructured":"Griffis, H.M., et al.: Use of social media across us hospitals: descriptive analysis of adoption and utilization. J. Med. Internet Res. 16(11), e3758 (2014)","journal-title":"J. Med. Internet Res."},{"key":"15_CR11","doi-asserted-by":"crossref","unstructured":"Gupta, A., Lamba, H., Kumaraguru, P., Joshi, A.: Faking sandy: characterizing and identifying fake images on twitter during hurricane sandy. In: Proceedings of the 22nd International Conference on World Wide Web, pp. 729\u2013736 (2013)","DOI":"10.1145\/2487788.2488033"},{"key":"15_CR12","doi-asserted-by":"crossref","unstructured":"Liu, X., Troncy, R., Huet, B.: Using social media to identify events. In: Proceedings of the 3rd ACM SIGMM International Workshop on Social Media, pp. 3\u20138 (2011)","DOI":"10.1145\/2072609.2072613"},{"issue":"1","key":"15_CR13","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1109\/TSC.2016.2542068","volume":"11","author":"S Mistry","year":"2016","unstructured":"Mistry, S., Bouguettaya, A., Dong, H., Qin, A.K.: Metaheuristic optimization for long-term IAAS service composition. IEEE Trans. Serv. Comput. 11(1), 131\u2013143 (2016)","journal-title":"IEEE Trans. Serv. Comput."},{"key":"15_CR14","unstructured":"Noakes, D.: Database of images from various digital cameras (2019). https:\/\/github.com\/drewnoakes\/metadata-extractor-images"},{"key":"15_CR15","series-title":"Studies in Computational Intelligence","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/978-3-030-90087-8_6","volume-title":"Combating Fake News with Computational Intelligence Techniques","author":"M Patel","year":"2022","unstructured":"Patel, M., Padiya, J., Singh, M.: Fake news detection using machine learning and natural language processing. In: Lahby, M., Pathan, A.-S.K., Maleh, Y., Yafooz, W.M.S. (eds.) Combating Fake News with Computational Intelligence Techniques. SCI, vol. 1001, pp. 127\u2013148. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-030-90087-8_6"},{"key":"15_CR16","doi-asserted-by":"crossref","unstructured":"Qian, S., Shen, C., Zhang, J.: Fighting cheapfakes: using a digital media literacy intervention to motivate reverse search of out-of-context visual misinformation. J. Comput.-Mediated Commun. 28(1), zmac024 (2023)","DOI":"10.1093\/jcmc\/zmac024"},{"key":"15_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2021.111240","volume":"151","author":"SA Rizvi","year":"2021","unstructured":"Rizvi, S.A., Umair, M., Cheema, M.A.: Clustering of countries for covid-19 cases based on disease prevalence, health systems and environmental indicators. Chaos Solitons Fractals 151, 111240 (2021)","journal-title":"Chaos Solitons Fractals"},{"key":"15_CR18","doi-asserted-by":"crossref","unstructured":"Saez-Trumper, D.: Fake tweet buster: a webtool to identify users promoting fake news on twitter. In: Proceedings of the 25th ACM Conference on Hypertext and Social Media, pp. 316\u2013317 (2014)","DOI":"10.1145\/2631775.2631786"},{"key":"15_CR19","doi-asserted-by":"crossref","unstructured":"Shahzad, H.F., Rustam, F., Flores, E.S., Lu\u00eds Vidal Maz\u00f3n, J., de la Torre Diez, I., Ashraf, I.: A review of image processing techniques for deepfakes. Sensors 22(12), 4556 (2022)","DOI":"10.3390\/s22124556"},{"issue":"2","key":"15_CR20","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1177\/1461444818799526","volume":"21","author":"C Shen","year":"2019","unstructured":"Shen, C., Kasra, M., Pan, W., Bassett, G.A., Malloch, Y., O\u2019Brien, J.F.: Fake images: the effects of source, intermediary, and digital media literacy on contextual assessment of image credibility online. New Media Soc. 21(2), 438\u2013463 (2019)","journal-title":"New Media Soc."},{"key":"15_CR21","doi-asserted-by":"crossref","unstructured":"Umair, M., Afzal, B., Khan, A., Rehman, A.U., Sekercioglu, Y.A., Shah, G.A.: Self-configurable hybrid energy management system for smart buildings. In: 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), pp. 1241\u20131246. IEEE (2018)","DOI":"10.1109\/ICARCV.2018.8581354"},{"key":"15_CR22","volume":"39","author":"M Umair","year":"2023","unstructured":"Umair, M., Cheema, M.A., Afzal, B., Shah, G.: Energy management of smart homes over fog-based IoT architecture. Sustain. Comput. Inf. Syst. 39, 100898 (2023)","journal-title":"Sustain. Comput. Inf. Syst."},{"key":"15_CR23","doi-asserted-by":"crossref","unstructured":"Umair, M., Saeed, Z., Ahmad, M., Amir, H., Akmal, B., Ahmad, N.: Multi-class classification of bi-lingual SMS using Naive Bayes algorithm. In: 2020 IEEE 23rd International Multitopic Conference (INMIC), pp. 1\u20135. IEEE (2020)","DOI":"10.1109\/INMIC50486.2020.9318153"},{"key":"15_CR24","doi-asserted-by":"crossref","unstructured":"Umair, M., Shah, G.A.: Energy management of smart homes. In: 2020 IEEE International Conference on Smart Computing (SMARTCOMP), pp. 247\u2013249. IEEE (2020)","DOI":"10.1109\/SMARTCOMP50058.2020.00054"},{"issue":"2","key":"15_CR25","first-page":"40","volume":"7","author":"F Zimmer","year":"2019","unstructured":"Zimmer, F., Scheibe, K., Stock, M., Stock, W.G.: Fake news in social media: bad algorithms or biased users? J. Inf. Sci. Theory Pract. 7(2), 40\u201353 (2019)","journal-title":"J. Inf. Sci. Theory Pract."}],"container-title":["Lecture Notes in Computer Science","Service-Oriented Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-48424-7_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,21]],"date-time":"2023-11-21T20:17:57Z","timestamp":1700597877000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-48424-7_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031484230","9783031484247"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-48424-7_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"20 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSOC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Service-Oriented Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rome","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icsoc2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icsoc2023.diag.uniroma1.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"ConfTool","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"208","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"35","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"10","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"17% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"other papers accepted: 3 industry full papers, 3 keynote abstracts (in the front matter)","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}