Conference Publication Details
Mandatory Fields
Porwol, L,Hassan, I,Ojo, A,Breslin, J,Tambouris, E,Panagiotopoulos, P,Saebo, O,Tarabanis, K,Wimmer, MA,Milano, M,Pardo, T
7th IFIP 8.5 International Conference on Electronic Participation
A knowledge extraction and management component to support spontaneous participation
2015
January
Published
1
WOS: 1 ()
Optional Fields
e-Participation Citizen-led e-Participation Information extraction (IE) Natural Language Processing (NLP) Public services e-Government DESIGN SCIENCE RESEARCH SOCIAL MEDIA EPARTICIPATION
Saebo O.,Tarabanis K.,Milano M.,Pardo T.A.,Tambouris E.,Wimmer M.A.,Panagiotopoulos P.
68
80
Thessaloniki, Greece
30-AUG-15
02-SEP-15
Harnessing spontaneous contributions of citizens on Social Media and networking sites is a major feature of the next generation citizen-led e-Participation paradigm. However, extracting information of interest from Social Media streams is a challenging task and requires support from domain specific language resources such as lexica. This work describes our efforts at developing a Knowledge Extraction and Management component which employs a lexicon for extracting information related to public services in Social Media contents or streams as part of a holistic technology infrastructure for citizen-led e-Participation. Our approach consists of three basic steps (1) acquisition and refinement of public service catalogues, (2) organization of the public service names into a lexicon based on different semantic similarity measures and (3) development of a dictionary-based Named Entity Recognizer (NER) or "spotter" based on the lexicon. We evaluate the performance of the NER solution supported by contextual information generated by two well-known general-purpose information NER tools (DBpedia Spotlight and Alchemy) on a dataset of tweets. Results show that our strategy to domain specific information extraction from Social Media is effective. We conclude with a scenario on how our approach could be scaled-up to extract other types of information from citizen discussions on Social Media.
10.1007/978-3-319-22500-5_6
Grant Details
Publication Themes
Informatics, Physical and Computational Sciences