ABSTRACT
During the past decade, there has been growing interest among researchers in informal learning at scale, particularly in the area of expert finding. These platforms have played a fundamental role in facilitating informal learning at scale, by providing access to diverse expertise and knowledge resources that might not otherwise be available to learners. Based on the encountered gaps in expert identification in Question & Answer (Q&A) portals, we inspect the feasibility of identifying data science experts in Reddit using the activity behaviour of every user, including Natural Language Processing (NLP), crowdsourced and user features sets. We also examine the impact of using only expert and non-expert classes versus three classes additionally including the out-of-scope class. Our findings can be used for distinguishing different types of users in Reddit, creating a recommendation system, identifying unreliable users or social bots in the early stage and reducing their influence.
- Aabdelaziz. 2021. Best & Most Popular Forums, Message Boards & Online Communities. https://it-maniacs.com/best-and-most-popular-forums-message-boards-and-online-communities-top-30/. Online; accessed 10 February 2022.Google Scholar
- Navedanjum Ansari and Rajesh Sharma. 2020. Identifying Semantically Duplicate Questions Using Data Science Approach: A Quora Case Study. arXiv preprint arXiv:2004.11694 (2020). https://doi.org/10.48550/arXiv.2004.11694Google Scholar
- Gerd Berget and Andrew MacFarlane. 2020. What is known about the impact of impairments on information seeking and searching? Journal of the Association for Information Science and Technology, Vol. 71, 5 (2020), 596--611. https://doi.org/10.1002/asi.24256Google ScholarDigital Library
- James Max Christensen. 2021. Student Preferences and Decisions for Online or In-Person Class Sessions in Blended Learning. (2021).Google Scholar
- Ethan Fast, Binbin Chen, and Michael S. Bernstein. 2016. Empath: Understanding Topic Signals in Large-Scale Text. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI '16). Association for Computing Machinery, New York, NY, USA, 4647--4657. https://doi.org/10.1145/2858036.2858535Google ScholarDigital Library
- Janice D. Gobert, Michael Sao Pedro, Juelaila Raziuddin, and Ryan S. Baker. 2013. From Log Files to Assessment Metrics: Measuring Students' Science Inquiry Skills Using Educational Data Mining. Journal of the Learning Sciences, Vol. 22, 4 (2013), 521--563. https://doi.org/10.1080/10508406.2013.837391Google ScholarCross Ref
- Mark Graham and William H Dutton. 2019. Society and the internet: How networks of information and communication are changing our lives. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199661992.001.0001Google Scholar
- Wern Han Lim, Mark James Carman, and Sze-Meng Jojo Wong. 2017. Estimating Relative User Expertise for Content Quality Prediction on Reddit. In Proceedings of the 28th ACM Conference on Hypertext and Social Media (Prague, Czech Republic) (HT '17). Association for Computing Machinery, New York, NY, USA, 55--64. https://doi.org/10.1145/3078714.3078720Google ScholarDigital Library
- Gloria Nishimwe, Sam Kamali, Eden Gatesi, and Rex Wong. 2022. Assessing the Perceptions and Preferences between Online and In-Person Classroom Learning among University Students in Rwanda. Journal of Service Science and Management, Vol. 15, 1 (2022), 23--34. https://doi.org/10.4236/jssm.2022.151003.Google ScholarCross Ref
- Sumanth Patil and Kyumin Lee. 2016. Detecting experts on Quora: by their activity, quality of answers, linguistic characteristics and temporal behaviors. Social network analysis and mining, Vol. 6, 1 (2016), 5. https://doi.org/10.1007/s13278-015-0313-xGoogle Scholar
- Nicholas Proferes, Naiyan Jones, Sarah Gilbert, Casey Fiesler, and Michael Zimmer. 2021. Studying Reddit: A Systematic Overview of Disciplines, Approaches, Methods, and Ethics. Social Media Society, Vol. 7, 2 (2021), 20563051211019004. https://doi.org/10.1177/20563051211019004Google ScholarCross Ref
- Sofia Strukova, José A. Ruipérez-Valiente, and Félix Gómez Mármol. 2022. A Survey on Data-Driven Evaluation of Competencies and Capabilities across Multimedia Environments. International Journal of Interactive Multimedia and Artificial Intelligence (2022). https://doi.org/10.9781/ijimai.2022.10.004Google ScholarCross Ref
- Magdeline M. Temban, Tan Kim Hua, and Nur Ehsan Mohd Said. 2021. Exploring Informal Learning Opportunities via YouTube Kids among Children During COVID-19. Academic Journal of Interdisciplinary Studies, Vol. 10, 3 (May 2021), 272. https://doi.org/10.36941/ajis-2021-0083Google ScholarCross Ref
- Sha Yuan, Yu Zhang, Jie Tang, Wendy Hall, and Juan Bautista Cabotà. 2020. Expert finding in community question answering: a review. Artificial Intelligence Review, Vol. 53, 2 (2020), 843--874. https://doi.org/10.1007/s10462-018-09680--6Google ScholarDigital Library
- Mattia Zago, Pantaleone Nespoli, Dimitrios Papamartzivanos, Manuel Gil Perez, Felix Gomez Marmol, Georgios Kambourakis, and Gregorio Martinez Perez. 2019. Screening Out Social Bots Interference: Are There Any Silver Bullets? IEEE Communications Magazine, Vol. 57, 8 (2019), 98--104. https://doi.org/10.1109/MCOM.2019.1800520Google ScholarDigital Library
Index Terms
- Towards the Identification of Experts in Informal Learning Portals at Scale
Recommendations
Informal Learning Communities: The Other Massive Open Online 'C'
L@S '20: Proceedings of the Seventh ACM Conference on Learning @ ScaleWhile the literature on learning at scale has largely focused on MOOCs, online degree programs, and AI techniques for supporting scalable learning experiences, informal learning communities have been relatively underrepresented. None-theless, these ...
Computational approaches to detect experts in distributed online communities: a case study on Reddit
AbstractThe irreplaceable key to the triumph of Question & Answer (Q & A) platforms is their users providing high-quality answers to the challenging questions posted across various topics of interest. From more than a decade, the expert finding problem ...
Integrating machine learning with knowledge acquisition through direct interaction with domain experts
Knowledge elicitation from experts and empirical machine learning are two distinct approaches to knowledge acquisition with differing and mutually complementary capabilities. Learning apprentices have provided environments in which a knowledge engineer ...
Comments