Page 141 - AIH-1-3
P. 141

Artificial Intelligence in Health                                    ADRD caregiver experiences on Reddit



            8.   Vu M, Mangal R, Stead T, Lopez-Ortiz C, Ganti L. Impact      doi: 10.1145/2133806.2133826
               of Alzheimer’s disease on caregivers in the United States.   19.  Grootendorst MR. BERTopic: Neural topic modeling with a
               Health Psychol Res. 2022;10(3):37454.
                                                                  class-based TF-IDF procedure. ArXiv. 2022.
               doi: 10.52965/001c.37454
                                                                  doi: 10.48550/arXiv.2203.05794
            9.   Sołtys A, Tyburski E. Predictors of mental health problems in   20.  Hutto CJ, Gilbert E. VADER: A Parsimonious Rule-based
               formal and informal caregivers of patients with Alzheimer’s   Model  for  Sentiment  Analysis  of  Social  Media  Text.  In:
               disease. BMC Psychiatry. 2020;20(1):435.
                                                                  Proceedings of the  8  International Conference on Weblogs
                                                                                 th
               doi: 10.1186/s12888-020-02822-7                    and Social Media. ICWSM; 2015.
            10.  Shoults CC, Rutherford MW, Kemp AS, et al. Analysis of   21.  Laureate CDP, Buntine W, Linger H. A systematic review of
               caregiver burden expressed in social media discussions. Int J   the use of topic models for short text social media analysis.
               Environ Res Public Health. 2023;20(3):1933.        Artif Intell Rev. 2023;56:14223-14255.
               doi: 10.3390/ijerph20031933                        doi: 10.1007/s10462-023-10471-x
            11.  Lobo EH, Johnson T, Frølich A, et al. Utilization of social   22.  Kherwa P, Bansal P. Topic modeling: A  comprehensive
               media communities for caregiver information support in   review. EAI Endorsed Trans Scalable Inf Syst. 2019;7(24):e2.
               stroke recovery: An analysis of content and interactions.
               PLoS One. 2022;17(1):e0262919.                     doi: 10.4108/eai.13-7-2018.159623
                                                               23.  Ramamoorthy T, Kulothungan V, Mappillairaju B. Topic
               doi: 10.1371/journal.pone.0262919
                                                                  modeling and social network analysis approach to explore
            12.  Zapcic I, Fabbri M, Karandikar S. Using Reddit as a source for   diabetes discourse on Twitter in India.  Front Artif Intell.
               recruiting participants for in-depth and phenomenological   2024;7:1329185.
               research. Int J Qual Methods. 2023;22:16094069231162674.
                                                                  doi: 10.3389/frai.2024.1329185
               doi: 10.1177/16094069231162674
                                                               24.  Yue L, Chen W, Li X, Zuo W, Yin M. A survey of sentiment
            13.  Ni C, Malin B, Song L, Jefferson A, Commiskey P, Yin Z.   analysis in social media. Knowl Inf Syst. 2019;60:617-663.
               “Rough Day … Need a Hug”: Learning challenges and
               experiences of the Alzheimer’s disease and related dementia      doi: 10.1007/s10115-018-1236-4
               caregivers on Reddit. Proc Int AAAI Conf Web Soc Media.   25.  Rodríguez-Ibánez M, Casánez-Ventura A, Castejón-Mateos F,
               2022;16(1):711-722.                                Cuenca-Jiménez, PM. A review on sentiment analysis from
                                                                  social media platforms. Expert Syst Appl. 2023;223:119862.
               doi: 10.1609/icwsm.v16i1.19328
                                                                  doi: 10.1016/j.eswa.2023.119862
            14.  Bird S, Klein, E, Loper, E. Natural Language Processing with
               Python: Analyzing Text with the Natural Language Toolkit.   26.  Wankhade M, Rao ACS, Kulkarni C. A survey on sentiment
               United States: O’Reilly Media, Inc.; 2009.         analysis methods, applications, and challenges. Artif Intell
                                                                  Rev. 2022;55:5731-5780.
            15.  Méndez JR, Iglesias EL, Fdez-Riverola F, Díaz F,
               Corchado JM. Tokenising, Stemming and Stopword Removal      doi: 10.1007/s10462-022-10144-1
               on Anti-spam Filtering Domain. Heidelberg: Springer Berlin;   27.  Caschera MC, Ferri F, Grifoni P. Sentiment Analysis from
               2006. p. 449-458.
                                                                  Textual to Multimodal Features in Digital Environments.
            16.  Honnibal M, Montani I, Van Landeghem S, Boyd A. spaCy:   In:  Proceedings of the 8   International Conference on
                                                                                      th
               Industrial-strength Natural Language Processing in Python.   Management of  Digital EcoSystems  (MEDES).  New  York,
               United States: Zenodo; 2020.                       USA: Association for Computing Machinery; 2016.
                                                                  p. 137-144.
            17.  Murakami  A,  Thompson  P,  Hunston  S,  Vajn  D.  What  is
               this corpus about?’: Using topic modelling to explore a      doi: 10.1145/3012071.3012089
               specialised corpus. Corpora. 2017;12:243-277.
                                                               28.  Xu QA, Chang V, Jayne C. A  systematic review of social
               doi: 10.3366/cor.2017.0118                         media-based Sentiment analysis: Emerging trends and
                                                                  challenges. Decis Anal J. 2022;3:100073.
            18.  Blei DM. Probabilistic topic models.  Commun ACM.
               2012;55(4):77-84.                                  doi: 10.1016/j.dajour.2022.100073











            Volume 1 Issue 3 (2024)                        135                               doi: 10.36922/aih.3075
   136   137   138   139   140   141   142   143   144