Notice bibliographique
Résumé
The COVID-19 pandemic forced the organizers of the IEEE/ACM conference on advances in social network analysis and mining (ASONAM) to go for virtual conference two years 2020 and 2021. It was not easy to handle the program over these two years because the speakers were widespread in all parts of the world with different time zones. It was not possible to get everyone together at the same time. For some sessions speakers were coming in to present then leaving to go back to sleep because they were forced to wake up and present even after mid-night in their time zone. All of this convinced the organizers that virtual conferences will not work for a real international conference; it might be acceptable for local or regional conferences. However, even by passing the time zone problem will not help solving the major problem or socialization and discussion beyond what is presented at the conferences. This will not be effective without in person attending. Realizing this need, we decided to move back to face-to-face in person participation in 2022. However, the unclear situation of COVID-19 in early 2022 did not help us to go all in person. To stay on the safe side, we decided to go hybrid for 2022 with in person component hosted by Istanbul Medipol University. Only after we completed the conference, we realized that hybrid is the option which should be avoided. It is hard to satisfy two groups of participants simultaneously. The local organizers end up investing their time and effort for lower number of in-person participants. This uncertainty in the organization modality has influenced the number of submissions which decreased compared to the previous years. However, the organizers decided to reduce the size of the conference in 2022 to avoid sacrificing the quality, keeping acceptance rate below 20%. This helped maintaining the acceptance rate which has stabilized around 13-18% since ASONAM was organized in Istanbul, Turkey in 2012. Indeed, Athens was the city where ASONAM was born in 2009 and Istanbul was the city where ASONAM in 2012 showed first signals of maturity and stability in terms of the number of submissions, acceptance rate and participation; the same high quality has been enforced again in Istanbul in 2022. We are happy to see the stability sustained and ASONAM kept its permanent position among top tier international conferences. Every year, authors of all papers presented at ASONAM, and the co-located events are invited to submit expanded versions of their manuscripts to the prestigious SNAM journal, NetMAHIB journal, or the LNSN series which are characterized by their high visibility and fast processing of submissions. Special thanks to Springer Nature for their continuous support since ASONAM started in 2009 and for having their prestigious venues which have been well integrated with ASONAM to the benefit of both parties.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,010 | 0,006 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,020 | 0,013 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,097 | 0,150 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».