Reviewer has chosen to be AnonymousOverall Impression:
UndecidedTechnical Quality of the paper:
Unable to judgePresentation:
Lack of noveltyData availability:
With exceptions that are admissible according to the data availability guidelines, all used and produced data are FAIR and openly available in established data repositoriesLength of the manuscript:
The length of this manuscript is about right
Summary of paper in a few sentences:
The paper “SSIX Big Data Technologies and Methods for Leveraging Social Sentiment Data in Multiple Business Domains” presents a research project which aims to provide tools for sentiment analysis of social media and news data to European SMEs. The project’s main focus is finance applications, where indices based on social sentiment will assist investment decision making.
The paper is an extension of the publication “Social Sentiment Indices Powered by X-scores” .
The main extensions are:
- A description of the SSIX architecture (Section 3)
- Two usage scenarios (Sections 4.1 and 4.2)
- A description of the concept of sentiment analysis, and a description of four software libraries which provide sentiment analysis functionality for SSIX (Section 6.2)
- An extension of the planned business case study presented in  and two additional planned business case studies. (Section 7)
 Davis, Brian, et al. "Social sentiment indices powered by X-scores." ALLDATA 2016 (2016): 21.
Reasons to accept:
- Overall, the paper is well written and the different aspects and steps of the research project are described in sufficient detail.
- The proposed system fills a gap regarding the availability of easily accessible and customizable tools for sentiment analysis of large scale social media and news data.
- The presented figures are intuitive and contribute greatly to readability of the paper and to a better understanding of the proposed project.
- The business case studies and usage scenarios demonstrate that the system has the potential to meet the business needs of SMEs.
Reasons to reject:
- In my opinion, the delta to  is not large enough to warrant a new publication. Large parts of the paper are nearly identical to  (including the introduction, related work, the description of SSIX templates, big social and news data management as well as significant parts of other sections).
- This paper was submitted as a research paper. However, it describes a planned software system and there are no experiments and no evaluation of the system. (While the authors state that the four sentiment analysis libraries described in Section 6.2 “were evaluated in a qualitative nature on a Twitter data sample”, neither the sample nor the process of evaluation is described.)
- It is unclear which parts of this system, if any, are already implemented.
Clarification on “Suggested decision: Undecided”: The decision whether this manuscript should be accepted for publication should be based largely on the journal’s policy on
- how much accepted papers should differ from existing publications, and
- whether a description of a planned software system should be accepted as a research paper.
Clarification on “Technical Quality: Unable to judge”: No quantitative experiments or results are reported in the paper.
Below are some minor remarks on those sections of the paper which do not appear in :
- Section 3 would benefit from a short introduction.
- The usage scenarios would benefit from additional references, e.g. studies where social media sentiment has been used for real-time polling.
- In Section 6.2, it should be clarified under which circumstances which sentiment analyzer should be used.
- Even though the business case studies are well presented, it would be interesting to know how the new set of tools provided by SSIX integrates with the existing infrastructure of the business partners.
- Section 1: “The European research project Social Sentiment Indices powered by X-Scores
(SSIX), seeks to assist” -> remove comma
- Section 6: peopl’s -> people’s