What makes information in online consumer reviews diagnostic over time? The role of review relevancy, factuality, currency, source credibility and ranking score

Online consumer reviews (OCRs) have become one of the most helpful and influential information in consumers purchase decisions. However, the proliferation of OCRs has made it difficult for consumers to orientate themselves with the wealth of reviews available. Therefore, it is paramount for online organizations to understand the determinants of perceived information diagnosticity in OCRs. In this study, we investigate consumer perceptions and we adopt the Elaboration Likelihood Model to analyze the influence of central (long, relevant, current, and factual OCRs) and peripheral cues (source credibility, overall ranking scores) on perceived information diagnosticity (PID). We consider the potential moderating effect of consumer involvement, and tested the robustness of the theoretical framework across time. Based on two surveys carried out in 2011 and in 2016, this study demonstrates the dynamic nature of the antecedents of PID in e-WOM. We found that long reviews are not perceived as helpful, while relevant and current reviews as well as overall ranking scores are perceived as diagnostic information in both samples. The significance of the predicting power of review factuality and source credibility has evolved over time. Both central (review quality dimensions) and peripheral cues (ranking score) were found to influence PID in high-involvement decisions

Genome-Wide Association between Branch Point Properties and Alternative Splicing

The branch point (BP) is one of the three obligatory signals required for pre-mRNA splicing. In mammals, the degeneracy of the motif combined with the lack of a large set of experimentally verified BPs complicates the task of modeling it in silico, and therefore of predicting the location of natural BPs. Consequently, BPs have been disregarded in a considerable fraction of the genome-wide studies on the regulation of splicing in mammals. We present a new computational approach for mammalian BP prediction. Using sequence conservation and positional bias we obtained a set of motifs with good agreement with U2 snRNA binding stability. Using a Support Vector Machine algorithm, we created a model complemented with polypyrimidine tract features, which considerably improves the prediction accuracy over previously published methods. Applying our algorithm to human introns, we show that BP position is highly dependent on the presence of AG dinucleotides in the 3′ end of introns, with distance to the 3′ splice site and BP strength strongly correlating with alternative splicing. Furthermore, experimental BP mapping for five exons preceded by long AG-dinucleotide exclusion zones revealed that, for a given intron, more than one BP can be chosen throughout the course of splicing. Finally, the comparison between exons of different evolutionary ages and pseudo exons suggests a key role of the BP in the pathway of exon creation in human. Our computational and experimental analyses suggest that BP recognition is more flexible than previously assumed, and it appears highly dependent on the presence of downstream polypyrimidine tracts. The reported association between BP features and the splicing outcome suggests that this, so far disregarded but yet crucial, element buries information that can complement current acceptor site models

An “In-Depth” Description of the Small Non-coding RNA Population of Schistosoma japonicum Schistosomulum

Parasitic flatworms of the genus Schistosoma are the causative agents of schistosomiasis, which afflicts more than 200 million people yearly in tropical regions of South America, Asia and Africa. A promising approach to the control of this and many other diseases involves the application of our understanding of small non-coding RNA function to the design of safe and effective means of treatment. In a previous study, we identified five conserved miRNAs from the adult stage of Schistosoma japonicum. Here, we applied Illumina Solexa high-throughput sequencing methods (deep sequencing) to investigate the small RNAs expressed in S. japonicum schistosomulum (3 weeks post-infection). This has allowed us to examine over four million sequence reads including both frequently and infrequently represented members of the RNA population. Thus we have identified 20 conserved miRNA families that have orthologs in well-studied model organisms and 16 miRNA that appear to be specific to Schistosoma. We have also observed minor amounts of heterogeneity in both 3′ and 5′ terminal positions of some miRNA as well as RNA fragments resulting from the processing of miRNA precursor. An investigation of the genomic arrangement of the 36 identified miRNA revealed that seven were tightly linked in two clusters. We also identified members of the small RNA population whose structure indicates that they are part of an endogenously derived RNA silencing pathway, as evidenced by their extensive complementarities with retrotransposon and retrovirus-related Pol polyprotein from transposon

Integration of Expressed Sequence Tag Data Flanking Predicted RNA Secondary Structures Facilitates Novel Non-Coding RNA Discovery

Many computational methods have been used to predict novel non-coding RNAs (ncRNAs), but none, to our knowledge, have explicitly investigated the impact of integrating existing cDNA-based Expressed Sequence Tag (EST) data that flank structural RNA predictions. To determine whether flanking EST data can assist in microRNA (miRNA) prediction, we identified genomic sites encoding putative miRNAs by combining functional RNA predictions with flanking ESTs data in a model consistent with miRNAs undergoing cleavage during maturation. In both human and mouse genomes, we observed that the inclusion of flanking ESTs adjacent to and not overlapping predicted miRNAs significantly improved the performance of various methods of miRNA prediction, including direct high-throughput sequencing of small RNA libraries. We analyzed the expression of hundreds of miRNAs predicted to be expressed during myogenic differentiation using a customized microarray and identified several known and predicted myogenic miRNA hairpins. Our results indicate that integrating ESTs flanking structural RNA predictions improves the quality of cleaved miRNA predictions and suggest that this strategy can be used to predict other non-coding RNAs undergoing cleavage during maturation