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This dataset has been collected thanks to the funding of the European Association for Machine Translation (EAMT) in its Sponsorship for Students Activities 2021. The name of the research project funded was "Machine Translation User Experience (MTUX): The Neglected Element in MT". The dataset contains the information about the interaction of 15 professional translators with different machine translation post-editing modalities (namely, traditional and interactive post-editing). Results include MTUX and translation quality and productivity scores.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 1 |

Views provided by UsageCounts