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Attention Score in Context
| Title |
Evaluating Hierarchical Structure in Music Annotations
|
|---|---|
| Published in |
Frontiers in Psychology, August 2017
|
| DOI | 10.3389/fpsyg.2017.01337 |
| Pubmed ID | |
| Authors |
Brian McFee, Oriol Nieto, Morwaread M. Farbood, Juan Pablo Bello |
| Abstract |
Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for "flat" descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 40% |
| Switzerland | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 40 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 33% |
| Researcher | 9 | 23% |
| Student > Master | 4 | 10% |
| Student > Postgraduate | 2 | 5% |
| Student > Doctoral Student | 1 | 3% |
| Other | 4 | 10% |
| Unknown | 7 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 12 | 30% |
| Arts and Humanities | 4 | 10% |
| Neuroscience | 3 | 8% |
| Materials Science | 2 | 5% |
| Psychology | 2 | 5% |
| Other | 8 | 20% |
| Unknown | 9 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 September 2017.
All research outputs
#14,060,054
of 24,049,457 outputs
Outputs from Frontiers in Psychology
#13,332
of 32,282 outputs
Outputs of similar age
#159,512
of 320,726 outputs
Outputs of similar age from Frontiers in Psychology
#334
of 584 outputs
Altmetric has tracked 24,049,457 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 32,282 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.8. This one has gotten more attention than average, scoring higher than 57% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 320,726 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 584 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.