{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:39:43Z","timestamp":1753882783152,"version":"3.41.2"},"reference-count":43,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2014,7,1]],"date-time":"2014-07-01T00:00:00Z","timestamp":1404172800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Big Data &amp; Society"],"published-print":{"date-parts":[[2014,7,1]]},"abstract":"<jats:p> Though full of promise, Big Data research success is often contingent on access to the newest, most advanced, and often expensive hardware systems and the expertise needed to build and implement such systems. As a result, the accessibility of the growing number of Big Data-capable technology solutions has often been the preserve of business analytics. Pay as you store\/process services like Amazon Web Services have opened up possibilities for smaller scale Big Data projects. There is high demand for this type of research in the digital humanities and digital sociology, for example. However, scholars are increasingly finding themselves at a disadvantage as available data sets of interest continue to grow in size and complexity. Without a large amount of funding or the ability to form interdisciplinary partnerships, only a select few find themselves in the position to successfully engage Big Data. This article identifies several notable and popular Big Data technologies typically implemented using large and extremely powerful cloud-based systems and investigates the feasibility and utility of development of Big Data analytics systems implemented using low-cost commodity hardware in basic and easily maintainable configurations for use within academic social research. Through our investigation and experimental case study (in the growing field of social Twitter analytics), we found that not only are solutions like Cloudera\u2019s Hadoop feasible, but that they can also enable robust, deep, and fruitful research outcomes in a variety of use-case scenarios across the disciplines. <\/jats:p>","DOI":"10.1177\/2053951714559105","type":"journal-article","created":{"date-parts":[[2014,11,26]],"date-time":"2014-11-26T03:58:19Z","timestamp":1416974299000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":17,"title":["Big Data solutions on a small scale: Evaluating accessible high-performance computing for social research"],"prefix":"10.1177","volume":"1","author":[{"given":"Dhiraj","family":"Murthy","sequence":"first","affiliation":[{"name":"Goldsmiths, University of London, London, UK"}]},{"given":"Sawyer A","family":"Bowman","sequence":"additional","affiliation":[{"name":"Bowdoin College, Brunswick, ME, USA"}]}],"member":"179","published-online":{"date-parts":[[2014,11,25]]},"reference":[{"key":"bibr1-2053951714559105","unstructured":"Andrikopoulos V, Fehling C and Leymann F (2012) Designing for CAP \u2013 The effect of design decisions on the CAP properties of cloud-native applications. In: CLOSER, Porto, Portugal, 18 April."},{"key":"bibr2-2053951714559105","unstructured":"Apache Hadoop (2013) Apache Hive TM. Available at: https:\/\/hive.apache.org\/ (accessed 8 April 2013)."},{"key":"bibr3-2053951714559105","unstructured":"Associated Press (2013) Number of active users at Facebook over the years.\u2013 Yahoo! News, 1 May. Available at: http:\/\/bigstory.ap.org\/article\/number-active-users-facebook-over-years-5."},{"key":"bibr4-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/2378356.2378368"},{"key":"bibr5-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772889"},{"volume-title":"Querying JSON streams","year":"2010","author":"Bo Y","key":"bibr6-2053951714559105"},{"key":"bibr7-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/2247596.2247598"},{"key":"bibr8-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1080\/1369118X.2012.678878"},{"key":"bibr9-2053951714559105","unstructured":"Cloudera Inc. (n.d.) Cloudera standard. Available at: http:\/\/www.cloudera.com\/content\/cloudera\/en\/products\/cloudera-standard.html (accessed 10 June 2013)."},{"issue":"4","key":"bibr10-2053951714559105","first-page":"243","volume":"9","author":"Culnan MJ","year":"2010","journal-title":"MIS Quarterly Executive"},{"key":"bibr11-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/2465848.2465849"},{"key":"bibr12-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/2132876.2132888"},{"key":"bibr13-2053951714559105","doi-asserted-by":"publisher","DOI":"10.5749\/minnesota\/9780816677948.001.0001"},{"key":"bibr14-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/2377978.2377984"},{"key":"bibr15-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/2331042.2331058"},{"key":"bibr16-2053951714559105","unstructured":"Holt R (2013) Twitter in numbers. Telegraph, 21 March. Available at: http:\/\/www.telegraph.co.uk\/technology\/twitter\/9945505\/Twitter-in-numbers.html."},{"key":"bibr17-2053951714559105","unstructured":"Hurst N (2013) Visual guide to NoSQL systems. Nathan Hurst's Blog. Available at: http:\/\/blog.nahurst.com\/visual-guide-to-nosql-systems (28 July 2013)."},{"key":"bibr17a-2053951714559105","unstructured":"Instagram (2014) Instagram. Available at: http:\/\/instagram.com\/press\/ (accessed 24 October 14)."},{"volume-title":"In: Proceedings of the 2012 conference of the center for advanced studies on collaborative research","year":"2012","author":"Joshi K","key":"bibr18-2053951714559105"},{"key":"bibr19-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/2245276.2245364"},{"key":"bibr20-2053951714559105","doi-asserted-by":"crossref","unstructured":"Kim M and Lee H (2011) SMCC: Social media cloud computing model for developing SNS based on social media. In: Convergence and hybrid information technology. Daejeon, Korea: Springer, pp. 259-266.","DOI":"10.1007\/978-3-642-24106-2_34"},{"key":"bibr21-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/2063576.2063973"},{"key":"bibr22-2053951714559105","doi-asserted-by":"publisher","DOI":"10.14778\/2367502.2367516"},{"key":"bibr23-2053951714559105","doi-asserted-by":"crossref","unstructured":"Leetaru KH (2012) Towards HPC for the digital humanities, arts, and social sciences: Needs and challenges of adapting academic HPC for big data. In: 2012 IEEE 8th international conference on E-Science (e-Science), Chicago, IL, 8\u201312 October.","DOI":"10.1109\/eScience.2012.6404439"},{"key":"bibr24-2053951714559105","doi-asserted-by":"crossref","unstructured":"Manovich L (2011) Trending: The promises and the challenges of big social data. In: Gold MK (ed.) Debates in the digital humanities. Minneapolis: University of Minnesota Press, pp. 460\u2013475.","DOI":"10.5749\/minnesota\/9780816677948.003.0047"},{"key":"bibr25-2053951714559105","unstructured":"Mayer-Schonberger V and Cukier K (2013) Big data: A revolution that will transform how we live, work, and think. New York, NY: Houghton Mifflin Harcourt."},{"key":"bibr26-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2465290"},{"volume-title":"Twitter: Social Communication in the Twitter Age","year":"2013","author":"Murthy D","key":"bibr27-2053951714559105"},{"key":"bibr28a-2053951714559105","unstructured":"Murthy D, Gross A and Pensavalle A (forthcoming) Urban Social Media Demographics: An Exploration of Twitter use in Major American Cities, Forthcoming manuscript (contact author for manuscript copy)."},{"key":"bibr28-2053951714559105","unstructured":"Nance C, Losser T, Iype R, et\u00a0al. (2013) NOSQL VS RDBMS \u2013 Why there is room for both. In: Proceedings of the Southern Association for Information Systems Conference, Savannah, GA, USA, 8\u20139 March."},{"key":"bibr29-2053951714559105","volume-title":"Analyzing Twitter Data with Apache Hadoop. Apache Hadoop for the Enterprise,","volume":"2013","author":"Natkins J","year":"2012"},{"key":"bibr30-2053951714559105","volume-title":"Analyzing Twitter Data with Apache Hadoop, Part 2: Gathering Data with Flume. Apache Hadoop for the Enterprise,","volume":"2013","author":"Natkins J","year":"2012"},{"key":"bibr31-2053951714559105","volume-title":"Analyzing Twitter Data With Apache Hadoop, Part 3: Querying Semi-structured Data with Apache Hive. Apache Hadoop for the Enterprise,","volume":"2013","author":"Natkins J","year":"2012"},{"issue":"1","key":"bibr32-2053951714559105","first-page":"15","volume":"11","author":"Padhy RP","year":"2011","journal-title":"International Journal of Advanced Engineering Science and Technologies"},{"key":"bibr33-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/2380718.2380748"},{"key":"bibr34-2053951714559105","unstructured":"Preotiuc-Pietro D, Samangooei S, Cohn T, et\u00a0al. (2012) Trendminer: An architecture for real time analysis of social media text. In: Proceedings of the workshop on real-time analysis and mining of social streams, Dublin, Ireland, 4 June."},{"key":"bibr35-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/1996413.1996415"},{"key":"bibr36-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/1653771.1653781"},{"key":"bibr37-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1145\/1871929.1871938"},{"key":"bibr38-2053951714559105","doi-asserted-by":"crossref","unstructured":"Stewart RJ, Trinder PW and Loidl H-W (2011) Comparing high level mapreduce query languages. In: Advanced Parallel Processing Technologies. Berlin, Heidelberg: Springer.","DOI":"10.1007\/978-3-642-24151-2_5"},{"key":"bibr39-2053951714559105","unstructured":"Twitter Inc (2013) Documentation: Twitter Developers. Available at: https:\/\/dev.twitter.com\/overview\/documentation (accessed 4 November 2014)."},{"key":"bibr40-2053951714559105","unstructured":"White T (2012) Hadoop: The Definitive Guide. Sebastopol, CA: O'Reilly."},{"key":"bibr41-2053951714559105","doi-asserted-by":"publisher","DOI":"10.1289\/ehp.10727"}],"container-title":["Big Data &amp; Society"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/2053951714559105","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/2053951714559105","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/2053951714559105","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,2]],"date-time":"2025-03-02T19:38:01Z","timestamp":1740944281000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/2053951714559105"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,7,1]]},"references-count":43,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2014,7,1]]}},"alternative-id":["10.1177\/2053951714559105"],"URL":"https:\/\/doi.org\/10.1177\/2053951714559105","relation":{},"ISSN":["2053-9517","2053-9517"],"issn-type":[{"type":"print","value":"2053-9517"},{"type":"electronic","value":"2053-9517"}],"subject":[],"published":{"date-parts":[[2014,7,1]]},"article-number":"2053951714559105"}}