Matches in SemOpenAlex for { <https://semopenalex.org/work/W3159454872> ?p ?o ?g. }
Showing items 1 to 85 of
85
with 100 items per page.
- W3159454872 endingPage "113581" @default.
- W3159454872 startingPage "113581" @default.
- W3159454872 abstract "Helpfulness prediction techniques have been widely incorporated into online decision support systems to identify high-quality reviews. Most current studies on helpfulness prediction assume that a review's helpfulness only relies on information from itself. In practice, however, consumers hardly process reviews independently because reviews are displayed in sequence; a review is more likely to be affected by its adjacent neighbors in the sequence, which is largely understudied. In this paper, we proposed the first end-to-end neural architecture to capture the missing interaction between reviews and their neighbors. Our model allows for a total of 12 (three selection × four aggregation) schemes that contextualize a review into the context clues learned from its neighbors. We evaluated our model on six domains of real-world online reviews against a series of state-of-the-art baselines. Experimental results confirm the influence of sequential neighbors on reviews and show that our model significantly outperforms the baselines by 1% to 5%. We further revealed how reviews are influenced by their neighbors during helpfulness perception via extensive analysis. The results and findings of our work provide theoretical contributions to the field of review helpfulness prediction and offer insights into practical decision support system design. • In practice, review helpfulness is hardly perceived independently since reviews are displayed in sequence. • We interact a review with its adjacent counterparts (i.e., neighbors) in the sequence during helpfulness prediction. • We design 12 (three selection × four aggregation) schemes to learn the context clues of a review from its neighbors. • Extensive experiments on six domains of real-world reviews show that our model reaches the new state-of-the-art. • We conduct further analysis on our model to investigate how reviews are influenced by their neighbors." @default.
- W3159454872 created "2021-05-10" @default.
- W3159454872 creator A5034544405 @default.
- W3159454872 creator A5034724899 @default.
- W3159454872 creator A5049750015 @default.
- W3159454872 creator A5076869167 @default.
- W3159454872 date "2021-09-01" @default.
- W3159454872 modified "2023-10-16" @default.
- W3159454872 title "Neighbor-aware review helpfulness prediction" @default.
- W3159454872 cites W1662133657 @default.
- W3159454872 cites W1977971300 @default.
- W3159454872 cites W1996921831 @default.
- W3159454872 cites W2002437555 @default.
- W3159454872 cites W2011879868 @default.
- W3159454872 cites W2012662675 @default.
- W3159454872 cites W2014101371 @default.
- W3159454872 cites W2019983800 @default.
- W3159454872 cites W2033276496 @default.
- W3159454872 cites W2072566632 @default.
- W3159454872 cites W2085821342 @default.
- W3159454872 cites W2090793409 @default.
- W3159454872 cites W2094800553 @default.
- W3159454872 cites W2172236729 @default.
- W3159454872 cites W2178002576 @default.
- W3159454872 cites W2523372191 @default.
- W3159454872 cites W2549817308 @default.
- W3159454872 cites W2593622378 @default.
- W3159454872 cites W2621795485 @default.
- W3159454872 cites W2762700563 @default.
- W3159454872 cites W2780946198 @default.
- W3159454872 cites W2952321608 @default.
- W3159454872 cites W2952451711 @default.
- W3159454872 cites W2965748866 @default.
- W3159454872 cites W2994658578 @default.
- W3159454872 cites W3007970570 @default.
- W3159454872 cites W3012839589 @default.
- W3159454872 cites W3018324781 @default.
- W3159454872 cites W3023022844 @default.
- W3159454872 cites W3081350537 @default.
- W3159454872 cites W3087228565 @default.
- W3159454872 cites W3123195011 @default.
- W3159454872 cites W3126357747 @default.
- W3159454872 cites W3138415243 @default.
- W3159454872 doi "https://doi.org/10.1016/j.dss.2021.113581" @default.
- W3159454872 hasPublicationYear "2021" @default.
- W3159454872 type Work @default.
- W3159454872 sameAs 3159454872 @default.
- W3159454872 citedByCount "12" @default.
- W3159454872 countsByYear W31594548722022 @default.
- W3159454872 countsByYear W31594548722023 @default.
- W3159454872 crossrefType "journal-article" @default.
- W3159454872 hasAuthorship W3159454872A5034544405 @default.
- W3159454872 hasAuthorship W3159454872A5034724899 @default.
- W3159454872 hasAuthorship W3159454872A5049750015 @default.
- W3159454872 hasAuthorship W3159454872A5076869167 @default.
- W3159454872 hasConcept C15744967 @default.
- W3159454872 hasConcept C2781265381 @default.
- W3159454872 hasConcept C41008148 @default.
- W3159454872 hasConcept C77805123 @default.
- W3159454872 hasConceptScore W3159454872C15744967 @default.
- W3159454872 hasConceptScore W3159454872C2781265381 @default.
- W3159454872 hasConceptScore W3159454872C41008148 @default.
- W3159454872 hasConceptScore W3159454872C77805123 @default.
- W3159454872 hasFunder F4320309893 @default.
- W3159454872 hasFunder F4320322942 @default.
- W3159454872 hasLocation W31594548721 @default.
- W3159454872 hasOpenAccess W3159454872 @default.
- W3159454872 hasPrimaryLocation W31594548721 @default.
- W3159454872 hasRelatedWork W2002563848 @default.
- W3159454872 hasRelatedWork W2092282862 @default.
- W3159454872 hasRelatedWork W2570913877 @default.
- W3159454872 hasRelatedWork W2611407113 @default.
- W3159454872 hasRelatedWork W2613921548 @default.
- W3159454872 hasRelatedWork W2748952813 @default.
- W3159454872 hasRelatedWork W2899084033 @default.
- W3159454872 hasRelatedWork W2934621214 @default.
- W3159454872 hasRelatedWork W4281847990 @default.
- W3159454872 hasRelatedWork W4285360723 @default.
- W3159454872 hasVolume "148" @default.
- W3159454872 isParatext "false" @default.
- W3159454872 isRetracted "false" @default.
- W3159454872 magId "3159454872" @default.
- W3159454872 workType "article" @default.