{"id":"https://openalex.org/W2104514557","doi":"https://doi.org/10.1145/2801948.2802010","title":"Sentiment analysis of greek tweets and hashtags using a sentiment lexicon","display_name":"Sentiment analysis of greek tweets and hashtags using a sentiment lexicon","publication_year":2015,"publication_date":"2015-09-22","ids":{"openalex":"https://openalex.org/W2104514557","doi":"https://doi.org/10.1145/2801948.2802010","mag":"2104514557"},"language":"en","primary_location":{"id":"doi:10.1145/2801948.2802010","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2801948.2802010","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th Panhellenic Conference on Informatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050542796","display_name":"Georgios Kalamatianos","orcid":"https://orcid.org/0000-0002-2435-1863"},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Georgios Kalamatianos","raw_affiliation_strings":["Democritus University of Thrace, Xanthi, Greece"],"affiliations":[{"raw_affiliation_string":"Democritus University of Thrace, Xanthi, Greece","institution_ids":["https://openalex.org/I147962203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051495888","display_name":"Dimitrios Mallis","orcid":null},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Dimitrios Mallis","raw_affiliation_strings":["Democritus University of Thrace, Xanthi, Greece"],"affiliations":[{"raw_affiliation_string":"Democritus University of Thrace, Xanthi, Greece","institution_ids":["https://openalex.org/I147962203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016041013","display_name":"Symeon Symeonidis","orcid":"https://orcid.org/0000-0002-3259-614X"},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Symeon Symeonidis","raw_affiliation_strings":["Democritus University of Thrace, Xanthi, Greece"],"affiliations":[{"raw_affiliation_string":"Democritus University of Thrace, Xanthi, Greece","institution_ids":["https://openalex.org/I147962203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058891144","display_name":"Avi Arampatzis","orcid":"https://orcid.org/0000-0003-2415-4592"},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Avi Arampatzis","raw_affiliation_strings":["Democritus University of Thrace, Xanthi, Greece"],"affiliations":[{"raw_affiliation_string":"Democritus University of Thrace, Xanthi, Greece","institution_ids":["https://openalex.org/I147962203"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5050542796"],"corresponding_institution_ids":["https://openalex.org/I147962203"],"apc_list":null,"apc_paid":null,"fwci":3.0201,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.92558598,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"63","last_page":"68"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.9039617776870728},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.8261176347732544},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7271767854690552},{"id":"https://openalex.org/keywords/sadness","display_name":"Sadness","score":0.7252575159072876},{"id":"https://openalex.org/keywords/disgust","display_name":"Disgust","score":0.7062758803367615},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.703656017780304},{"id":"https://openalex.org/keywords/microblogging","display_name":"Microblogging","score":0.677675724029541},{"id":"https://openalex.org/keywords/surprise","display_name":"Surprise","score":0.5314734578132629},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48911601305007935},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4843789041042328},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4774382710456848},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4640215039253235},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.4380807876586914},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.15504372119903564},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.14477673172950745}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.9039617776870728},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.8261176347732544},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7271767854690552},{"id":"https://openalex.org/C2779812673","wikidata":"https://www.wikidata.org/wiki/Q169251","display_name":"Sadness","level":3,"score":0.7252575159072876},{"id":"https://openalex.org/C2777375102","wikidata":"https://www.wikidata.org/wiki/Q208351","display_name":"Disgust","level":3,"score":0.7062758803367615},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.703656017780304},{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.677675724029541},{"id":"https://openalex.org/C2780343955","wikidata":"https://www.wikidata.org/wiki/Q333173","display_name":"Surprise","level":2,"score":0.5314734578132629},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48911601305007935},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4843789041042328},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4774382710456848},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4640215039253235},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.4380807876586914},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.15504372119903564},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.14477673172950745},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2801948.2802010","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2801948.2802010","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th Panhellenic Conference on Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W40549020","https://openalex.org/W80287495","https://openalex.org/W939190374","https://openalex.org/W2078396654","https://openalex.org/W2097726431","https://openalex.org/W2105468141","https://openalex.org/W2267835966","https://openalex.org/W4205184193","https://openalex.org/W4205989039","https://openalex.org/W6669996083"],"related_works":["https://openalex.org/W2120267809","https://openalex.org/W2955987787","https://openalex.org/W4238520549","https://openalex.org/W3216173459","https://openalex.org/W2794357331","https://openalex.org/W4242611441","https://openalex.org/W4242034606","https://openalex.org/W4402346481","https://openalex.org/W2037174948","https://openalex.org/W1540611520"],"abstract_inverted_index":{"The":[0,50],"rapid":[1],"growth":[2],"of":[3,15,21,39,67,79,87,111],"social":[4],"media":[5],"has":[6],"rendered":[7],"opinion":[8],"and":[9,29,73,100,119],"sentiment":[10,38,45,57,96,112],"mining":[11],"an":[12],"important":[13],"area":[14],"research":[16],"with":[17,122],"a":[18,56,84],"wide":[19],"range":[20],"applications.":[22],"We":[23,59],"focus":[24],"on":[25,55],"the":[26,30,65,77,109],"Greek":[27],"language":[28],"microblogging":[31],"platform":[32],"\"Twitter\",":[33],"investigating":[34],"methods":[35,52],"for":[36,46,63,116],"extracting":[37],"individual":[40],"tweets":[41],"as":[42],"well":[43],"population":[44],"different":[47],"subjects":[48],"(hashtags).":[49],"proposed":[51],"are":[53],"based":[54],"lexicon.":[58],"compare":[60],"several":[61],"approaches":[62],"measuring":[64],"intensity":[66,113],"\"Anger\",":[68],"\"Disgust\",":[69],"\"Fear\",":[70],"\"Happiness\",":[71],"\"Sadness\",":[72],"\"Surprise\".":[74],"To":[75],"evaluate":[76],"effectiveness":[78],"our":[80],"methods,":[81],"we":[82,107],"develop":[83],"benchmark":[85],"dataset":[86],"tweets,":[88],"manually":[89],"rated":[90],"by":[91],"two":[92],"humans.":[93],"Our":[94],"automated":[95],"results":[97],"seem":[98],"promising":[99],"correlate":[101],"to":[102],"real":[103],"user":[104],"sentiment.":[105],"Finally,":[106],"examine":[108],"variation":[110],"over":[114],"time":[115],"selected":[117],"hashtags,":[118],"associate":[120],"it":[121],"real-world":[123],"events.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
