A dataset of annotated free comments on the sensory perception of madeleines for benchmarking text mining techniquesRecherche.Data.Gouv
This dataset was created to investigate the impact of data collection modes and pre-processing techniques on the quality of free comment data related to consumers' sensory perceptions. A total of 200 consumers were recruited and divided into two groups of 100. Each group evaluated six madeleine...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
|
| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340924012125 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832576453881888768 |
|---|---|
| author | Michel Visalli Ronan Symoneaux Cécile Mursic Margaux Touret Flore Lourtioux Kipédène Coulibaly Benjamin Mahieu |
| author_facet | Michel Visalli Ronan Symoneaux Cécile Mursic Margaux Touret Flore Lourtioux Kipédène Coulibaly Benjamin Mahieu |
| author_sort | Michel Visalli |
| collection | DOAJ |
| description | This dataset was created to investigate the impact of data collection modes and pre-processing techniques on the quality of free comment data related to consumers' sensory perceptions. A total of 200 consumers were recruited and divided into two groups of 100. Each group evaluated six madeleine samples (five distinct samples and one replicate) in a sensory analysis laboratory, using different free comment data collection modes. Consumers in the first group provided only words or short expressions, while those in the second group used complete sentences. Additionally, participants reported their liking for each sample.The collected data provided valuable insights into the effectiveness of the free comment method in sensory evaluation of food products. They emphasized the importance of data pre-processing and demonstrated how the chosen techniques can impact the quality of the results. The dataset is based on real-world consumer data, showcasing how individuals naturally express their subjective perceptions. It features descriptions that reflect authentic consumer language, including informal expressions, incorrect phrasing, spelling errors, and unstructured sentences. This raw textual data has been annotated and translated into English. The dataset can therefore be repurposed to assess and compare the performance of different text mining, natural language processing and sentiment analysis algorithms in both French and English, as well as to drive innovations in AI tools for sensory and consumer research. |
| format | Article |
| id | doaj-art-08f37d9d095b4536bf87f7dbc8efe5c0 |
| institution | Kabale University |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-08f37d9d095b4536bf87f7dbc8efe5c02025-01-31T05:11:40ZengElsevierData in Brief2352-34092025-02-0158111250A dataset of annotated free comments on the sensory perception of madeleines for benchmarking text mining techniquesRecherche.Data.GouvMichel Visalli0Ronan Symoneaux1Cécile Mursic2Margaux Touret3Flore Lourtioux4Kipédène Coulibaly5Benjamin Mahieu6Centre des Sciences du Goût et de l'Alimentation, AgroSup Dijon, CNRS, INRAE, Université Bourgogne, F-21000 Dijon, France; INRAE, PROBE research infrastructure, ChemoSens facility, F-21000 Dijon, France; Corresponding author at: Centre des Sciences du Goût et de l'Alimentation, L'Institut Agro Dijon, CNRS, INRAE, Université Bourgogne, F-21000 Dijon, France.GRAPPE, ESA, USC 1422 INRAE, SensoVeg, SFR 4207 QUASAV, 55 rue Rabelais, F-49007 Angers, FranceTechni'Sens, 17000 La Rochelle, FranceTechni'Sens, 17000 La Rochelle, FranceGRAPPE, ESA, USC 1422 INRAE, SensoVeg, SFR 4207 QUASAV, 55 rue Rabelais, F-49007 Angers, FranceCentre des Sciences du Goût et de l'Alimentation, AgroSup Dijon, CNRS, INRAE, Université Bourgogne, F-21000 Dijon, France; INRAE, PROBE research infrastructure, ChemoSens facility, F-21000 Dijon, FranceOniris, INRAE, StatSC, 44300 Nantes, FranceThis dataset was created to investigate the impact of data collection modes and pre-processing techniques on the quality of free comment data related to consumers' sensory perceptions. A total of 200 consumers were recruited and divided into two groups of 100. Each group evaluated six madeleine samples (five distinct samples and one replicate) in a sensory analysis laboratory, using different free comment data collection modes. Consumers in the first group provided only words or short expressions, while those in the second group used complete sentences. Additionally, participants reported their liking for each sample.The collected data provided valuable insights into the effectiveness of the free comment method in sensory evaluation of food products. They emphasized the importance of data pre-processing and demonstrated how the chosen techniques can impact the quality of the results. The dataset is based on real-world consumer data, showcasing how individuals naturally express their subjective perceptions. It features descriptions that reflect authentic consumer language, including informal expressions, incorrect phrasing, spelling errors, and unstructured sentences. This raw textual data has been annotated and translated into English. The dataset can therefore be repurposed to assess and compare the performance of different text mining, natural language processing and sentiment analysis algorithms in both French and English, as well as to drive innovations in AI tools for sensory and consumer research.http://www.sciencedirect.com/science/article/pii/S2352340924012125Open ended questionsNatural language processingSensory evaluationDrivers of liking |
| spellingShingle | Michel Visalli Ronan Symoneaux Cécile Mursic Margaux Touret Flore Lourtioux Kipédène Coulibaly Benjamin Mahieu A dataset of annotated free comments on the sensory perception of madeleines for benchmarking text mining techniquesRecherche.Data.Gouv Data in Brief Open ended questions Natural language processing Sensory evaluation Drivers of liking |
| title | A dataset of annotated free comments on the sensory perception of madeleines for benchmarking text mining techniquesRecherche.Data.Gouv |
| title_full | A dataset of annotated free comments on the sensory perception of madeleines for benchmarking text mining techniquesRecherche.Data.Gouv |
| title_fullStr | A dataset of annotated free comments on the sensory perception of madeleines for benchmarking text mining techniquesRecherche.Data.Gouv |
| title_full_unstemmed | A dataset of annotated free comments on the sensory perception of madeleines for benchmarking text mining techniquesRecherche.Data.Gouv |
| title_short | A dataset of annotated free comments on the sensory perception of madeleines for benchmarking text mining techniquesRecherche.Data.Gouv |
| title_sort | dataset of annotated free comments on the sensory perception of madeleines for benchmarking text mining techniquesrecherche data gouv |
| topic | Open ended questions Natural language processing Sensory evaluation Drivers of liking |
| url | http://www.sciencedirect.com/science/article/pii/S2352340924012125 |
| work_keys_str_mv | AT michelvisalli adatasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT ronansymoneaux adatasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT cecilemursic adatasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT margauxtouret adatasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT florelourtioux adatasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT kipedenecoulibaly adatasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT benjaminmahieu adatasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT michelvisalli datasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT ronansymoneaux datasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT cecilemursic datasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT margauxtouret datasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT florelourtioux datasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT kipedenecoulibaly datasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv AT benjaminmahieu datasetofannotatedfreecommentsonthesensoryperceptionofmadeleinesforbenchmarkingtextminingtechniquesrecherchedatagouv |