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- Ekström, Axel G., et al.
(författare)
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The Search Query Filter Bubble : Effect of User Ideology on Political Leaning of Search Results Through Query Selection
- 2024
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Ingår i: Information Communication and Society. - : Routledge. - 1369-118X .- 1468-4462. ; 27:5, s. 878-894
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Tidskriftsartikel (refereegranskat)abstract
- It is commonly assumed that personalization technologies used by Google for the purpose of tailoring search results for individual users create filter bubbles, which reinforce users’ political views. Surprisingly, empirical evidence for a personalization-induced filter bubble has not been forthcoming. Here, we investigate whether filter bubbles may result instead from a searcher’s choice of search queries. In the first experiment, participants rated the left-right leaning of 48 queries (search strings), 6 for each of 8 topics (abortion, benefits, climate change, sex equality, immigration, nuclear family, Islam, and taxation). An independent sample of participants were then asked to select one of these queries for each of the 8 topics. With the exception of the topic of Islam, participants were significantly more likely to select a query corresponding to their own political leaning, compared to other queries, explaining between 12% and 39% of the variance. A second experiment investigated the effect of the political leaning of the same queries on the overall political leaning of Search Engine Result Pages (SERPs) in Google Search. The top six results of each SERP were rated collectively by a third group of participants, explaining 36.3% of the variance across all 48 search terms (p
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| 2. |
- Elowsson, Anders, et al.
(författare)
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Modelling the Speed of Music Using Features from Harmonic/Percussive Separated Audio
- 2013
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Ingår i: Proceedings of the 14th International Society for Music Information Retrieval Conference. - : International Society for Music Information Retrieval. - 9780615900650 ; , s. 481-486
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Konferensbidrag (refereegranskat)abstract
- One of the major parameters in music is the overall speed of a musical performance. In this study, a computational model of speed in music audio has been developed using a custom set of rhythmic features. Speed is often associ-ated with tempo, but as shown in this study, factors such as note density (onsets per second) and spectral flux are important as well. The original audio was first separated into a harmonic part and a percussive part and the fea-tures were extracted separately from the different layers. In previous studies, listeners had rated the speed of 136 songs, and the ratings were used in a regression to evalu-ate the validity of the model as well as to find appropriate features. The final models, consisting of 5 or 8 features, were able to explain about 90% of the variation in the training set, with little or no degradation for the test set.
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