{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T18:05:10Z","timestamp":1754157910028,"version":"3.41.2"},"reference-count":16,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2011,6,21]],"date-time":"2011-06-21T00:00:00Z","timestamp":1308614400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,6,21]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>Recent years have seen \u201creally simple syndication\u201d or \u201crich site summary\u201d(RSS) syndication of frequently updated content become ubiquitous across the internet. RSS's XML\u2010based format allows these data to be stored in a semi\u2010structured format but, despite the presence of online aggregators and readers, and the related work in clustering feeds and mining subjects by keywords, much potentially useful information present in RSS may remain undiscovered. This paper aims to address this issue in an experimental setting.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>This paper presents two distinct technologies which employ the semi\u2010structured nature of RSS content to allow users to mine information directly from raw RSS feeds: occurrence mining counts occurrences of text strings in feeds, whilst value mining mines structured ticker tape numeric data. It describes both technologies and their implementation in an experiment, where 35 students mined small numbers of RSS feeds and visualised the data mined.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>This paper analyses the results of the experiment and cites examples of data mined and visualisations produced. The subject matter of data mined is also explored and potential applications of the technologies are considered.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title><jats:p>The mining technologies proposed in this paper have been developed to mine textual and numeric data directly from feeds, but can be extended to mine other data types present in RSS and to include other variants like Atom.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>These technologies are seen to be applicable to data mining, the role of data and visualisations in social data analysis, issue tracking in news mining and time series analysis.<\/jats:p><\/jats:sec>","DOI":"10.1108\/17440081111141763","type":"journal-article","created":{"date-parts":[[2011,6,18]],"date-time":"2011-06-18T07:17:15Z","timestamp":1308381435000},"page":"105-129","source":"Crossref","is-referenced-by-count":3,"title":["Mining and visualising information from RSS feeds: a case study"],"prefix":"10.1108","volume":"7","author":[{"given":"Martin","family":"O'Shea","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark","family":"Levene","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2022012820052867600_b1","doi-asserted-by":"crossref","unstructured":"Ali, M.S., Consens, M.P. and Rizzolo, F. (2007), \u201cVisualizing structural patterns in web collections\u201d, WWW '07: Proceedings of the 16th International Conference on World Wide Web in Banff, Alberta, Canada, 2007, ACM, New York, NY, pp. 1333\u20104.","DOI":"10.1145\/1242572.1242836"},{"key":"key2022012820052867600_b2","unstructured":"Bray, T., Paoli, J., Sperberg\u2010McQueen, C.M., Maler, E. and Yeargeau, F. (2004), Extensible Markup Language (XML) 1.0, W3C Recommendation, 3rd ed., available at: www.w3.org\/TR\/\/REC\u2010xml\u201020040204\/."},{"key":"key2022012820052867600_b3","unstructured":"B\u00fcchner, A.G., Mulvenna, M.D., Anand, S.S., Baumgarten, M. and B\u00f6hm, R. (2000), \u201cData mining and XML: current and future issues\u201d, WISE '00: Proceedings of the First International Conference on Web Information Systems Engineering (WISE'00), Volume 2, IEEE Computer Society, Washington, DC, p. 2131."},{"key":"key2022012820052867600_b4","doi-asserted-by":"crossref","unstructured":"Chen, Y.R., Fabbrizio, G., Gibbon, D., Jora, S., Renger, B. and Wei, B. (2007), \u201cGeotracker: geospatial and temporal RSS navigation\u201d, WWW '07: Proceedings of the 16th international conference on World Wide Web in Banff, Alberta, Canada, 2007, ACM, New York, NY, pp. 41\u201050.","DOI":"10.1145\/1242572.1242579"},{"key":"key2022012820052867600_b5","doi-asserted-by":"crossref","unstructured":"Getahun, F., Tekli, J., Chbeir, R., Viviani, M. and Yetongnon, K. (2009), \u201cRelating RSS news\/items\u201d, ICWE '9: Proceedings of the 9th International Conference on Web Engineering in San Seb\u00e1stian, Spain, 2009, Springer\u2010Verlag, Berlin, pp. 442\u201052.","DOI":"10.1007\/978-3-642-02818-2_36"},{"key":"key2022012820052867600_b6","doi-asserted-by":"crossref","unstructured":"Hu, C. and Chou, C. (2009), \u201cRSS Watchdog: An instant event monitor on real online news streams\u201d, CIKM '09: Proceeding of the 18th ACM Conference on Information and Knowledge Management in Hong Kong, China, 2009, ACM, New York, NY, pp. 2097\u20108.","DOI":"10.1145\/1645953.1646321"},{"key":"key2022012820052867600_b7","doi-asserted-by":"crossref","unstructured":"Li, X., Yan, J., Deng, Z., Ji, L., Fan, W., Zhang, B. and Chen, Z. (2007), \u201cA novel clustering\u2010based RSS aggregator\u201d, WWW '07: Proceedings of the 16th International Conference on World Wide Web in Banff, Alberta, Canada, 2007, ACM, New York, NY, pp. 1309\u201010.","DOI":"10.1145\/1242572.1242824"},{"key":"key2022012820052867600_b8","doi-asserted-by":"crossref","unstructured":"Liu, B., Han, H., Noro, T. and Tokuda, T. (2009), \u201cPersonal news RSS feeds generation using existing news feeds\u201d, ICWE '9: Proceedings of the 9th International Conference on Web Engineering in San Seb\u00e1stian, Spain, 2009, Springer\u2010Verlag, Berlin, pp. 419\u201033.","DOI":"10.1007\/978-3-642-02818-2_34"},{"key":"key2022012820052867600_b9","doi-asserted-by":"crossref","unstructured":"Pera, M.S. and Ng, Y.\u2010K. 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(2010), \u201cCreate special domain news collections through summarization and classification\u201d, IEEJ Transactions on Electrical and Electronic Engineering, Vol. 5 No. 1, pp. 56\u201061.","DOI":"10.1002\/tee.20493"},{"key":"key2022012820052867600_b13","doi-asserted-by":"crossref","unstructured":"Thelwall, M., Prabowo, R. and Fairclough, R. (2006), \u201cAre raw RSS feeds suitable for broad issue scanning? A science concern case study\u201d, Journal of the American Society for Information Science and Technology, Vol. 57 No. 12, pp. 1644\u201054.","DOI":"10.1002\/asi.20334"},{"key":"key2022012820052867600_b14","doi-asserted-by":"crossref","unstructured":"Vi\u00e9gas, F.B., Wattenberg, M., Heer, J. and Agrawala, M. 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