  People unequivocally employ reviews to decide on purchasing an item or an
experience on the internet. In that regard, the growing significance and number
of opinions have led to the development of methods to assess their sentiment
content automatically. However, it is not straightforward for the models to
create a consensus value that embodies the agreement of the different reviews
and differentiates across equal ratings for an item. Based on the approach
proposed by Nguyen et al. in 2020, we derive a novel consensus value named
ConTrip that merges their consensus score and the overall rating of a platform
for an item. ConTrip lies in the rating range values, which makes it more
interpretable while maintaining the ability to differentiate across equally
rated experiences. ConTrip is implemented and freely available under MIT
license at https://github.com/pepebonet/contripscore
