Table 7 Sample of studies of data science as an object of study
From: Data science: developing theoretical contributions in information systems via text analytics
Title of O-type studies | Contribution | Goal |
|---|---|---|
Chandak, M. B. (2016). Role of big-data in classification and novel class detection in data streams. Journal of Big Data, 3(1), 5 | Artifact | Design |
Chopade, P., & Zhan, J. (2015). Structural and functional analytics for community detection in large-scale complex networks. Journal of Big Data, 2(1), 11 | Artifact | Design |
Fang, X., & Zhan, J. (2015). Sentiment analysis using product review data. Journal of Big Data, 2(1), 5 | Artifact | Design |
Hasanin, T., Khoshgoftaar, T. M., Leevy, J. L., & Seliya, N. (2019). Examining characteristics of predictive models with imbalanced big data. Journal of Big Data, 6(1), 69 | Theory and artifact | Prediction and design |
Kaur, A., & Datta, A. (2015). A novel algorithm for fast and scalable subspace clustering of high-dimensional data. Journal of Big Data, 2(1), 17 | Artifact | Design |
Khalilian, M., Mustapha, N., & Sulaiman, N. (2016). Data stream clustering by divide and conquer approach based on vector model. Journal of Big Data, 3(1), 1 | Artifact | Design |
Nagwani, N. K. (2015). Summarizing large text collection using topic modeling and clustering based on MapReduce framework. Journal of Big Data, 2(1), 6 | Artifact | Design |
O’Donovan, P., Leahy, K., Bruton, K., & O’Sullivan, D. T. J. (2015). An industrial big data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities. Journal of Big Data, 2(1), 25 | Theory and artifact | Prediction and design |
Pirouz, M., & Zhan, J. (2016). Optimized relativity search: Node reduction in personalized page rank estimation for large graphs. Journal of Big Data, 3(1), 12 | Artifact | Design |
Prusa, J. D., & Khoshgoftaar, T. M. (2017). Improving deep neural network design with new text data representations. Journal of Big Data, 4(1), 7 | Artifact | Design |
Sharma, S., & Toshniwal, D. (2017). Scalable two-phase co-occurring sensitive pattern hiding using MapReduce. Journal of Big Data, 4(1), 4 | Artifact | Design |
Yang, Y., Zhang, K., Wang, J., & Nguyen, Q. V. (2015). Cabinet Tree: An orthogonal enclosure approach to visualizing and exploring big data. Journal of Big Data, 2(1), 15 | Artifact | Design |
Young-Min, K. (2019). Feature visualization in comic artist classification using deep neural networks. Journal of Big Data, 6(1), 56 | Artifact | Design |
Zhang, H., Raitoharju, J., Kiranyaz, S., & Gabbouj, M. (2016). Limited random walk algorithm for big graph data clustering. Journal of Big Data, 3(1), 26 | Artifact | Design |
Brynjolfsson, E., Geva, T., & Reichman, S. (2016). Crowd-Squared: Amplifying the Predictive Power of Search Trend Data. MIS Quarterly, 40(4), 941–962 | Artifact | Design |
Martens, D., Provost, F., Clark, J., & Junqué de Fortuny, E. (2016). Mining massive fine-grained behavior data to improve predictive analytics. MIS Quarterly, 40(4), 869–888 | Theory and artifact | Prediction and design |