Finding Experts in Social Media Data using a Hybrid Approach
Several approaches to the problem of expert finding have emerged in computer science research. In this work, three of these approaches - content analysis, social graph analysis and the use of Semantic Web technologies are examined. An integrated set of system requirements is then developed that uses all three approaches in one hybrid approach. To show the practicality of this hybrid approach, a usable prototype expert finding system called ExpertQuest is developed using a modern functional programming language (Clojure) to query social media data and Linked Data. This system is evaluated and discussed. Finally, a discussion and conclusions are presented which describe the benefits and shortcomings of the hybrid approach and the technologies used in this work.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts
Social networks are vital for information sharing, especially in the health sector for discussing diseases and treatments. These platforms, however, often feature posts as brief texts, posing challenges for Artificial In…
Knowledge Graph EmbeddingsKnowledge GraphsWord EmbeddingsDoes Geo-co-location Matter? A Case Study of Public Health Conversations during COVID-19
Social media platforms like Twitter (now X) have been pivotal in information dissemination and public engagement, especially during COVID-19. A key goal for public health experts was to encourage prosocial behavior that …
Issues and Perspectives from 10,000 Annotated Financial Social Media Data
In this paper, we investigate the annotation of financial social media data from several angles. We present Fin-SoMe, a dataset with 10,000 labeled financial tweets annotated by experts from both the front desk and the m…
Combining Hierachical VAEs with LLMs for clinically meaningful timeline summarisation in social media
We introduce a hybrid abstractive summarisation approach combining hierarchical VAE with LLMs (LlaMA-2) to produce clinically meaningful summaries from social media user timelines, appropriate for mental health monitorin…
Can AI Outperform Human Experts in Creating Social Media Creatives?
Artificial Intelligence has outperformed human experts in functional tasks such as chess and baduk. How about creative tasks? This paper evaluates AI's capability in the creative domain compared to human experts, which l…