SSIX Big Data Technologies and Methods for Leveraging Social Sentiment Data in Multiple Business Domains

Tracking #: 428-1408

Responsible editor: 

Tobias Kuhn

Submission Type: 

Research Paper


Social Sentiment Indices powered by X-Scores (SSIX) aims to provide European SMEs with a collection of easy to interpret tools to analyse and understand social media users' attitudes for any given topic. These sentiment characteristics can be exploited to help SMEs operate more efficiently resulting in increased revenues. Social media data represents a combined measure of thoughts and views touching every area of life. SSIX will search and index conversations taking place on social network services, such as Twitter, StockTwits and Facebook, together with the most reliable and trustworthy news agencies, newspapers, blogs and industry publications. A statistical framework of qualitative and quantitative parameters called X-Scores will power SSIX. Classification and scoring of content will be done using this framework, regardless of language, locale or data architecture. The X-Scores framework will interpret economically significant sentiment signals in social media conversations producing sentiment metrics, such as momentum, breadth, topic frequency, volatility and historical comparison. These metrics will create commercially viable social sentiment indexes, which can be tailored to any domain of interest. By enabling European SMEs to analyse and leverage social sentiment in their discipline, SSIX will facilitate the creation of innovative products and services by enhancing the investment decision making process, thus assisting in generating increased revenue while also minimising risk exposure.



  • Reviewed

Data repository URLs: 


Date of Submission: 

Thursday, February 23, 2017

Date of Decision: 

Thursday, June 1, 2017

Nanopublication URLs:



Solicited Reviews:


Meta-Review by Editor

I agree with the reviewers that the following two problems need to be addressed:

1. The paper needs an evaluation to be a research paper, or needs to be written more generally (not just about SSIX) to be a position paper. At the moment, it reads like a "recycled grant proposal" [reviewer 1].

2. The difference to the ALLDATA paper is at the moment not sufficient to warrant a new publication, as the additions seem to cover only very low-level technical details and business-related aspects. I cannot see any scientifically interesting additions.

The paper should be turned either into a proper research paper by adding an evaluation, or be turned into a position paper by abstracting away from SSIX and its details and by providing a view on "Technologies and Methods for Leveraging Social Sentiment Data" in general. In the latter case, the paper should also be significantly shortened.

Also note that all authors need to be entered in the submission system (this is currently not the case).

Tobias Kuhn (