Framing Metadata for Social Media and Community Development Meaning as FAIRdata

Agus Pamuji, Muzaki Muzaki, Rina Rindanah

Abstract


Interconnected devices of internet-based have drived to the real community to interact within the cyberspace. As the responsibility, we had been gathering artefact declared that public applications in the community interaction will have been evolving exponentially. To comprehend the project FAIRdata with metadata that trigerred on the end-user, User-centered design in the social media had released and to ensure sustainable community in the developing context. In this working, we attempt to illuminate the concept of metadata which extracted from publicly interactive application (e.g. social media), and the FAIRdata was defined as the fundamental of framework. Technically, the strategic of worked project remains considering due to the fact that descriptive is the major elicitation to reveal how to envisage both community building and social media obviusly indicated open-data with metadata. As a result, metadata of social media on the web platform to be indicated as open-intelegence which related the providing the amount of data, and the escalating performance with interoperabilit aspect, this project of initial building data rapidly was reinforcing the capacity in the next time of the  research. Therefore, predictive project recommendations to delve FAIRdata, estimated workflow of framework about explaining data of public application in the several platform will have conducted across the institutionals or agency  with more selective

Keywords


Social Media, Community Development, FAIRdata, Metadata, Interoperability

Full Text:

PDF

References


Abebe, M. A., Tekli, J., Getahun, F., Chbeir, R., & Tekli, G. (2020). Generic metadata representation framework for social-based event detection, description, and linkage. Knowledge-Based Systems, 188, 104817.

Acker, A., & Kreisberg, A. (2020). Social media data archives in an API-driven world. Archival Science, 20(2), 105-123

Adarsh, V., Kumar, P. A., Lavanya, V., & Gangadharan, G. R. (2023). Fair and explainable depression detection in social media. Information Processing & Management, 60(1), 103168.

Alhassun, A. S., & Rassam, M. A. (2022). A combined text-based and metadata-based deep-learning framework for the detection of spam accounts on the social media platform twitter. Processes, 10(3), 439.

Bhatta, K. D., & Joshi, B. R. (2023). Community collaboration with tourism stakeholders: Issues and challenges to promote sustainable community development in Annapurna Sanctuary Trail, Nepal. Saudi J Eng Technol, 8(6), 146-154.

Bogue, M. A., Ball, R. L., Philip, V. M., Walton, D. O., Dunn, M. H., Kolishovski, G., ... & Chesler, E. J. (2023). Mouse Phenome Database: towards a more FAIR-compliant and TRUST-worthy data repository and tool suite for phenotypes and genotypes. Nucleic acids research, 51(D1), D1067-D1074.

Bowers, A. J., & Choi, Y. (2023). Building school data equity, infrastructure, and capacity through FAIR data standards: Findable, Accessible, Interoperable, and Reusable. Educational Researcher, 52(7), 450-458.

Brinson, L. C., Bartolo, L. M., Blaiszik, B., Elbert, D., Foster, I., Strachan, A., & Voorhees, P. W. (2024). Community action on FAIR data will fuel a revolution in materials research. MRS bulletin, 49(1), 12-16.

Cetinkaya, Y. M., Gürlek, M., Toroslu, I. H., & Karagöz, P. (2022). Twitter account classification using account metadata: organizationvs. individual. Turkish Journal of Electrical Engineering and Computer Sciences, 30(4), 1404-1418.

Chen, P., Wu, L., & Wang, L. (2023). AI fairness in data management and analytics: A review on challenges, methodologies and applications. Applied Sciences, 13(18), 10258.

Chen, Y., Sherren, K., Smit, M., & Lee, K. Y. (2023). Using social media images as data in social science research. New Media & Society, 25(4), 849-871.

da Mota, V. T., & Pickering, C. (2021). Assessing the popularity of urban beaches using metadata from social media images as a rapid tool for coastal management. Ocean & Coastal Management, 203, 105519.

da Silva Santos, L. O. B., Burger, K., Kaliyaperumal, R., & Wilkinson, M. D. (2023). FAIR data point: a FAIR-oriented approach for metadata publication. Data Intelligence, 5(1), 163-183.

Darcy, S., Maxwell, H., Edwards, M., & Almond, B. (2023). Disability inclusion in beach precincts: beach for all abilities–a community development approach through a social relational model of disability lens. Sport Management Review, 26(1), 1-23.

Fox, N., Graham, L. J., Eigenbrod, F., Bullock, J. M., & Parks, K. E. (2021). Enriching social media data allows a more robust representation of cultural ecosystem services. Ecosystem Services, 50, 101328.

Fukuda, H., Ishiguro, C., Ono, R., & Kiyohara, K. (2023). The Longevity Improvement & Fair Evidence (LIFE) study: overview of the study design and baseline participant profile. Journal of epidemiology, 33(8), 428-437.

González-Sendino, R., Serrano, E., & Bajo, J. (2024). Mitigating bias in artificial intelligence: Fair data generation via causal models for transparent and explainable decision-making. Future Generation Computer Systems, 155, 384-401.

Gupta, K., Oladimeji, D., Varol, C., Rasheed, A., & Shahshidhar, N. (2023). A comprehensive survey on artifact recovery from social media platforms: approaches and future research directions. Information, 14(12), 629.

Hsiao, Y. T., & Wang, S. M. (2023, July). Exploring Web3 for Applying to Online Health Community Development Using Text Analysis. In 2023 International Conference on Consumer Electronics-Taiwan (ICCE-Taiwan) (pp. 369-370). IEEE.

Hussain, S., Shahzad, M., Appolloni, A., & Xuetong, W. (2023). The impact of public infrastructure project delays on sustainable community development. Environmental Science and Pollution Research, 30(14), 40519-40533.

Jiang, M., Roth, H. R., Li, W., Yang, D., Zhao, C., Nath, V., ... & Xu, Z. (2023). Fair federated medical image segmentation via client contribution estimation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 16302-16311).

Jung, W., Kim, D., Nam, S., & Zhu, Y. (2023). Suicidality detection on social media using metadata and text feature extraction and machine learning. Archives of suicide research, 27(1), 13-28.

Khader, M., & Karam, M. (2023). Assessing the Effectiveness of Masking and Encryption in Safeguarding the Identity of Social Media Publishers from Advanced Metadata Analysis. Data, 8(6), 105.

Kim, D., Jung, W., Jiang, T., & Zhu, Y. (2023). An exploratory study of medical journal’s Twitter use: metadata, networks, and content analyses. Journal of medical Internet research, 25, e43521.

Kirchknopf, A., Slijepčević, D., & Zeppelzauer, M. (2021, June). Multimodal detection of information disorder from social media. In 2021 International conference on content-based multimedia indexing (CBMI) (pp. 1-4). IEEE.

Kwon, K. H., Shao, C., & Nah, S. (2021). Localized social media and civic life: Motivations, trust, and civic participation in local community contexts. Journal of Information Technology & Politics, 18(1), 55-69.

Lai, J. C. M., Wang, C. L., & Hsieh, M. Y. (2023). A Research on Diversified Applications of Technological Education in the Development of Rural District Community Development Associations. Engineering Proceedings, 38(1), 18.

Li, C., Xing, W., & Leite, W. (2024). Using fair AI to predict students’ math learning outcomes in an online platform. Interactive Learning Environments, 32(3), 1117-1136.

Musen, M. A., O’Connor, M. J., Schultes, E., Martínez-Romero, M., Hardi, J., & Graybeal, J. (2022). Modeling community standards for metadata as templates makes data FAIR. Scientific Data, 9(1), 696.

Niu, H., & Silva, E. A. (2023). Understanding temporal and spatial patterns of urban activities across demographic groups through geotagged social media data. Computers, Environment and Urban Systems, 100, 101934.

Ohwofasa, A., Dhami, M., Tian, B., Winefield, C., & On, S. L. (2023). Environmental influences on microbial community development during organic pinot noir wine production in outdoor and indoor fermentation conditions. Heliyon, 9(5).

Ouwerkerk, J., Rasche, H., Spalding, J. D., Hiltemann, S., & Stubbs, A. P. (2024). FAIR data retrieval for sensitive clinical research data in Galaxy. GigaScience, 13, giad099.

Pandya, A., Oussalah, M., Monachesi, P., & Kostakos, P. (2020). On the use of distributed semantics of tweet metadata for user age prediction. Future Generation Computer Systems, 102, 437-452

Quarati, A. (2023). Open government data: usage trends and metadata quality. Journal of Information Science, 49(4), 887-910.

Ross, G. M. S., Zhao, Y., Bosman, A. J., Geballa-Koukoula, A., Zhou, H., Elliott, C. T., ... & Salentijn, G. I. (2023). Best practices and current implementation of emerging smartphone-based (bio) sensors–part 1: data handling and ethics. TrAC Trends in Analytical Chemistry, 158, 116863.

Struckmann, S., Mariño, J., Kasbohm, E., Salogni, E., & Schmidt, C. O. (2024). dataquieR 2: An updated R package for FAIR data quality assessments in observational studies and electronic health record data. Journal of Open Source Software, 9(98), 6581.

Tao, Y., & Wang, W. H. (2023). Fair privacy: how college students perceive fair privacy protection in online datasets. Information, Communication & Society, 26(5), 974-989.

Teo, C. T., Abdollahzadeh, M., & Cheung, N. M. (2023, June). Fair generative models via transfer learning. In Proceedings of the AAAI conference on artificial intelligence (Vol. 37, No. 2, pp. 2429-2437).

Umair, M., Bouguettaya, A., Lakhdari, A., Ouzzani, M., & Liu, Y. (2024). Exif2Vec: A Framework to Ascertain Untrustworthy Crowdsourced Images Using Metadata. ACM Transactions on the Web, 18(3), 1-27.

Vlassenroot, E., Chambers, S., Lieber, S., Michel, A., Geeraert, F., Pranger, J., ... & Mechant, P. (2021). Web-archiving and social media: an exploratory analysis: call for papers digital humanities and web archives–a special issue of international journal of digital humanities. International Journal of Digital Humanities, 2(1), 107-128.

Wagner, M. M., Hogan, W. R., Levander, J. D., & Diller, M. (2024). Towards Machine-FAIR: Representing software and datasets to facilitate reuse and scientific discovery by machines. Journal of Biomedical Informatics, 154, 104647.

Waititu, P. (2021). Creating community based environmental awareness with social media: A Kenyan perspective. Southern African Journal of Environmental Education, 37.

Whang, S. E., Roh, Y., Song, H., & Lee, J. G. (2023). Data collection and quality challenges in deep learning: A data-centric ai perspective. The VLDB Journal, 32(4), 791-813.


Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 International Conference of Da'wa and Islamic Communication