Sentiment classification for early detection of health alerts in the chemical textile domain

In the chemical textile domain experts have to analyse chemical components and substances that might be harmful for their usage in clothing and textiles. Part of this analysis is performed searching opinions and reports people have expressed concerning these products in the Social Web. However, this type of information on the Internet is not as frequent for this domain as for others, so its detection and classification is difficult and time-consuming. Consequently, problems associated to the use of chemical substances in textiles may not be detected early enough, and could lead to health problems, such as allergies or burns. In this paper, we propose a framework able to detect, retrieve, and classify subjective sentences related to the chemical textile domain, that could be integrated into a wider health surveillance system. We also describe the creation of several datasets with opinions from this domain, the experiments performed using machine learning techniques and different lexical resources such as WordNet, and the evaluation focusing on the sentiment classification, and complaint detection (i.e., negativity). Despite the challenges involved in this domain, our approach obtains promising results with an F-score of 65% for polarity classification and 82% for complaint detection.

Does the scientific evidence support the advertising claims made for products containing Lactobacillus casei and Bifidobacterium lactis? A systematic review

Background To analyse the scientific evidence that exists for the advertising claims made for two products containing Lactobacillus casei and Bifidobacterium lactis and to conduct a comparison between the published literature and what is presented in the corporate website. Methods Systematic review, using Medline through Pubmed and Embase. We included human clinical trials that exclusively measured the effect of Lactobacillus casei or Bifidobacterium lactis on a healthy population, and where the objective was related to the health claims made for certain products in advertising. We assessed the levels of evidence and the strength of the recommendation according to the classification criteria established by the Oxford Centre for Evidence Based Medicine (CEBM). We also assessed the outcomes of the studies published on the website that did not appear in the search. Results Of the 440 articles identified, 16 met the inclusion criteria. Only four (25%) of these presented a level of evidence of 1b and a recommendation grade of A, all corresponding to studies on product containing Bifidobacterium lactis, and only 12 of the 16 studies were published on the corporate website (47). Conclusions There is insufficient scientific evidence to support the health claims made for these products, especially in the case of product containing Lactobacillus casei.