Structured Literature Analysis Research Articles

Social media analytics – Challenges in topic discovery, data collection, and data preparation

Since an ever-increasing part of the population makes use of social media in their day-to-day lives, social media data is being analysed in many different disciplines. The social media analytics process involves four distinct steps, data discovery, collection, preparation, and analysis. While there is a great deal of literature on the challenges and difficulties involving specific data analysis methods, there hardly exists research on the stages of data discovery, collection, and preparation. To address this gap, we conducted an extended and structured literature analysis through which we identified challenges addressed and solutions proposed. The literature search revealed that the volume of data was most often cited as a challenge by researchers. In contrast, other categories have received less attention. Based on the results of the literature search, we discuss the most important challenges for researchers and present potential solutions. The findings are used to extend an existing framework on social media analytics. The article provides benefits for researchers and practitioners who wish to collect and analyse social media data.

Visual Interaction with Dimensionality Reduction: A Structured Literature Analysis.

Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data. For DR techniques to be useful in exploratory data analysis, they need to be adapted to human needs and domain-specific problems, ideally, interactively, and on-the-fly. Many visual analytics systems have already demonstrated the benefits of tightly integrating DR with interactive visualizations. Nevertheless, a general, structured understanding of this integration is missing. To address this, we systematically studied the visual analytics and visualization literature to investigate how analysts interact with automatic DR techniques. The results reveal seven common interaction scenarios that are amenable to interactive control such as specifying algorithmic constraints, selecting relevant features, or choosing among several DR algorithms. We investigate specific implementations of visual analysis systems integrating DR, and analyze ways that other machine learning methods have been combined with DR. Summarizing the results in a "human in the loop" process model provides a general lens for the evaluation of visual interactive DR systems. We apply the proposed model to study and classify several systems previously described in the literature, and to derive future research opportunities.

The incidence of implant fractures after knee arthroplasty.

This study aimed to evaluate the incidence of "implant" fractures after knee arthroplasty using clinical literature and worldwide arthroplasty registers. The hypothesis was that register datasets report higher rates of these rare complications than clinical studies. Calculations were based on the pooled incidence of revision operations after fractures of knee arthroplasties, comparing clinical studies published in MEDLINE-listed journals and annual reports from worldwide arthroplasty registers in a structured literature analysis based on a standardized methodology. Twelve clinical studies and datasets from six worldwide registers were included. Rates of fractures of knee arthroplasties were reported from 0.2 to 2.5% in clinical studies versus 0.02-0.17% in worldwide arthroplasty registers. Fractures of knee arthroplasty systems are rare complications, with clinical studies showing higher incidence rates than worldwide arthroplasty registries. Unicompartmental knee arthroplasty (UKA) implanted before 2000, constrained primary or revision constrained total knee arthroplasties, and patellar replacements showed the highest incidence of implant fracture. The results of this analysis can help clinicians to counsel patients on potential complications following knee arthroplasty. III.

Waste Electrical and Electronic Equipments versus End of Life Vehicles: A State of the Art Analysis and Quantification of Potential Profits

Waste Electrical and Electronic Equipments (WEEEs) and End of Life Vehicles (ELVs) are two of the main waste streams, after municipal solid wastes, both in volumes and growth rates terms. Even if their management begins to be adequately regulated almost worldwide, there are still clear lacks to be solved in many aspects. The aim of this paper is the comparison, through a structured literature analysis, of these waste streams under several perspectives, by evidencing current differences and potential commonalities. In addition, a quantification of potential profits rising from a joined management of different sources of PCBs is described in the last part of the paper.

Event-Driven Business Process Management: where are we now?

– The business operations of today's enterprises are heavily influenced by numerous of internal and external business events. With the Event Driven Architecture and particularly the Complex Event Processing (CEP), the technology required for identifying complex correlations in these large amounts of event data right after its appearance has already emerged. The resulting gain in operational transparency builds the foundation for (near) real-time reactions. This motivated extensive research activities especially in the field of Business Process Management (BPM), which essentially coined the term Event-Driven BPM (EDBPM). Now, several years after the advent of this new concept, the purpose of this paper is to shed light to the question: where are we now on our way towards a sophisticated adoption of the CEP technology within BPM? , – The research methodology of this paper is a structured literature analysis. It basically follows the procedure proposed by vom Brocke et al. (2009). This verified five-step process – entitled “Reconstructing the giant” – allowed a rigorous study. As a result, various research clusters were derived, whose state-of-the-art exposed existing research gaps within EDBPM. , – First of all, the paper provides a concise conceptual basis on different application possibilities of EDBPM. Afterwards, it synthesizes current research into six clusters and highlights most significant work within them. Finally, a research agenda is proposed to tackle existing research gaps to pave the way towards fully realizing the potentials of the paradigm. , – So far, a comparable study of the current state-of-the-art within EDBPM is non-existent. The findings of this paper, e.g. the proposed research agenda, help scholars to focus their research efforts on specific aspects that need to be considered in order to advance the adoption of the CEP technology within BPM.