Çağrı Toraman
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- ACM Transactions on Asian and Low-Resource Language Information Processing (1)
- ACM Transactions on Intelligent Systems and Technology (1)
- Information Processing and Management: an International Journal (1)
- Journal of Information Science (1)
- Journal of the Association for Information Science and Technology (1)
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- 2019 IEEE International Conference on Intelligence and Security Informatics (ISI) (3)
- Advances in Information Retrieval (1)
- AIRS'11: Proceedings of the 7th Asia conference on Information Retrieval Technology (1)
- ECIR'12: Proceedings of the 34th European conference on Advances in Information Retrieval (1)
- Past, Present, and Future on News Streams: Discovering Story Chains, Selecting Public Front-pages, and Filtering Microblogs for Predicting Public Reactions to News / Haber Akışlarında Geçmis, Günümüz ve Gelecek: Haber Zincirlerinin Keşfi, Anasayfaların Haber Seçimi, Habere Karşı Toplumsal Tepkinin Tahmini Için Mikroblog Filtrelenmesi (1)
- SIGIR '20: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (1)
- WebSci '22: Proceedings of the 14th ACM Web Science Conference 2022 (1)
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- research-articleOpen Access
Published By ACM
Published By ACM
Detecting Misinformation on Social Media using Community Insights and Contrastive Learning
Oguzhan Ozcelik
Department of Computer Engineering, Bilkent University, Ankara, Turkey and Aselsan Inc., Ankara, Turkey
,Cagri Toraman
Department of Computer Engineering, Middle East Technical University, Ankara, Turkey
,Fazli Can
Department of Computer Engineering, Bilkent University, Ankara, Turkey
ACM Transactions on Intelligent Systems and Technology, Volume 16, Issue 2•April 2025, Article No.: 38, pp 1-27 • https://doi.org/10.1145/3709009Social media users are more likely to be exposed to similar views and tend to avoid contrasting views, especially when they are part of a community of social media users. In this study, we investigate the presence of user communities and leverage them as ...
- 0Citation
- 373
- Downloads
MetricsTotal Citations0Total Downloads373Last 12 Months373Last 6 weeks194
- research-article
Published By ACM
Published By ACM
Impact of Tokenization on Language Models: An Analysis for Turkish
Cagri Toraman
Aselsan Research Center, Ankara, Turkey
,Eyup Halit Yilmaz
Aselsan Research Center, Ankara, Turkey
,Furkan Şahi̇nuç
Aselsan Research Center, Ankara, Turkey
,Oguzhan Ozcelik
Aselsan Research Center, Ankara, Turkey
ACM Transactions on Asian and Low-Resource Language Information Processing, Volume 22, Issue 4•April 2023, Article No.: 116, pp 1-21 • https://doi.org/10.1145/3578707Tokenization is an important text preprocessing step to prepare input tokens for deep language models. WordPiece and BPE are de facto methods employed by important models, such as BERT and GPT. However, the impact of tokenization can be different for ...
- 20Citation
- 1,473
- Downloads
MetricsTotal Citations20Total Downloads1,473Last 12 Months810Last 6 weeks82
- research-article
Named entity recognition in Turkish: A comparative study with detailed error analysis
Oguzhan Ozcelik
Aselsan Research Center, Yenimahalle, Ankara, 06200, Turkey
,Cagri Toraman
Aselsan Research Center, Yenimahalle, Ankara, 06200, Turkey
Information Processing and Management: an International Journal, Volume 59, Issue 6•Nov 2022 • https://doi.org/10.1016/j.ipm.2022.103065AbstractNamed entity recognition aims to detect pre-determined entity types in unstructured text. There is a limited number of studies on this task for low-resource languages such as Turkish. We provide a comprehensive study for Turkish named ...
Highlights- We implement 20 models and compare their performances on five datasets for Turkish named entity recognition.
- 2Citation
MetricsTotal Citations2
- short-paper
Published By ACM
Published By ACM
BlackLivesMatter 2020: An Analysis of Deleted and Suspended Users in Twitter
Cagri Toraman
Aselsan Research Center, Turkey
,Furkan Şahinuç
Aselsan Research Center, Turkey
,Eyup Halit Yilmaz
Aselsan Research Center, Turkey
WebSci '22: Proceedings of the 14th ACM Web Science Conference 2022•June 2022, pp 290-295• https://doi.org/10.1145/3501247.3531539After George Floyd’s death in May 2020, the volume of discussion in social media increased dramatically. A series of protests followed this tragic event, called as the 2020 BlackLivesMatter movement. Eventually, many user accounts are deleted by their ...
- 4Citation
- 172
- Downloads
MetricsTotal Citations4Total Downloads172Last 12 Months26Last 6 weeks1- 1
Supplementary MaterialWS22_S5_3.mp4
- Article
Tweet Length Matters: A Comparative Analysis on Topic Detection in Microblogs
Furkan Şahinuç
Aselsan Research Center, Ankara, Turkey
,Cagri Toraman
Aselsan Research Center, Ankara, Turkey
Advances in Information Retrieval•March 2021, pp 471-478• https://doi.org/10.1007/978-3-030-72240-1_50AbstractMicroblogs are characterized as short and informal text; and therefore sparse and noisy. To understand topic semantics of short text, supervised and unsupervised methods are investigated, including traditional bag-of-words and deep learning-based ...
- 0Citation
MetricsTotal Citations0
- short-paper
Published By ACM
Published By ACM
KLOOS: KL Divergence-based Out-of-Scope Intent Detection in Human-to-Machine Conversations
Eyup Halit Yilmaz
Aselsan Research Center, Ankara, Turkey
,Cagri Toraman
Aselsan Research Center, Ankara, Turkey
SIGIR '20: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval•July 2020, pp 2105-2108• https://doi.org/10.1145/3397271.3401318User intent is not restricted in human-to-machine conversations, and sometimes overshoots the scope of a designed system. Many tasks for understanding conversations require the elimination of such out-of-scope queries. We propose an out-of-scope intent ...
- 4Citation
- 375
- Downloads
MetricsTotal Citations4Total Downloads375Last 12 Months16Last 6 weeks1- 1
Supplementary Material3397271.3401318.mp4
- research-article
SimON-Feedback: An Iterative Algorithm for Performance Tuning in Online Social Simulation
Mehul Vora
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A
,Wingyan Chung
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A
,Cagri Toraman
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A
,Yifan Huang
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A
2019 IEEE International Conference on Intelligence and Security Informatics (ISI)•July 2019, pp 13-17• https://doi.org/10.1109/ISI.2019.8823438Simulation of human behaviour being an intrinsically difficult problem, no single algorithm or model can accurately simulate online social networks. One can obtain an optimal and reliable simulation only after combining several models focusing on diverse ...
- 0Citation
MetricsTotal Citations0
- research-article
A Deep Learning Approach to Modeling Temporal Social Networks on Reddit
Wingyan Chung
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A
,Cagri Toraman
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A
,Yifan Huang
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A
,Mehul Vora
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A
,Jinwei Liu
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A
2019 IEEE International Conference on Intelligence and Security Informatics (ISI)•July 2019, pp 68-73• https://doi.org/10.1109/ISI.2019.8823399As terrorists are losing against counter-terrorism efforts, they turn to manipulating cryptocurrency prices through online social communities to gain illicit profit to fund their operations. Modeling temporal online social networks (OSNs) of these ...
- 0Citation
MetricsTotal Citations0
- research-article
CrossSimON: A Novel Probabilistic Approach to Cross-Platform Online Social Network Simulation
Jinwei Liu
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A.
,Wingyan Chung
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A.
,Yifan Huang
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A.
,Cagri Toraman
School of Modeling, Simulation, and Training, University of Central Florida, Orlando, Florida, 32826, U.S.A.
2019 IEEE International Conference on Intelligence and Security Informatics (ISI)•July 2019, pp 7-12• https://doi.org/10.1109/ISI.2019.8823276The increasing popularity and diversity of online social networks (OSNs) have attracted more and more people to participate in multiple OSNs. Learning users' behavior and information diffusion across platforms is critical for cyber threat detection, but ...
- 1Citation
MetricsTotal Citations1
- research-article
Discovering story chains: A framework based on zigzagged search and news actors
Cagri Toraman
Bilkent Information Retrieval Group Computer Engineering Department, Bilkent University Ankara 06800 Turkey
,Fazli Can
Bilkent Information Retrieval Group Computer Engineering Department, Bilkent University Ankara 06800 Turkey
Journal of the Association for Information Science and Technology, Volume 68, Issue 12•December 2017, pp 2795-2808 • https://doi.org/10.1002/asi.23885A story chain is a set of related news articles that reveal how different events are connected. This study presents a framework for discovering story chains, given an input document, in a text collection. The framework has 3 complementary parts that i) ...
- 2Citation
MetricsTotal Citations2
- Doctoral Theses
Past, Present, and Future on News Streams: Discovering Story Chains, Selecting Public Front-pages, and Filtering Microblogs for Predicting Public Reactions to News / Haber Akışlarında Geçmis, Günümüz ve Gelecek: Haber Zincirlerinin Keşfi, Anasayfaların Haber Seçimi, Habere Karşı Toplumsal Tepkinin Tahmini Için Mikroblog Filtrelenmesi
Çağrı Toraman
Bilkent Universitesi (Turkey)
,Can, Fazlı
Bilkent Universitesi (Turkey)
,Altıngövde, i. Sengör
Bilkent Universitesi (Turkey)
,Erean, Gönenς
Bilkent Universitesi (Turkey)
,Güdükbay, Uğur
Bilkent Universitesi (Turkey)
,Ulusoy, Özgür
Bilkent Universitesi (Turkey)
AbstractNews streams have several research opportunities for the past, present, and future of events. The past hides relations among events and actors; the present reflects needs of news readers; and the future waits to be predicted. The thesis has three ...
- 0Citation
MetricsTotal Citations0
- research-article
A front-page news-selection algorithm based on topic modelling using raw text
Journal of Information Science, Volume 41, Issue 5•10 2015, pp 676-685 • https://doi.org/10.1177/0165551515589069Front-page news selection is the task of finding important news articles in news aggregators. In this study, we examine news selection for public front pages using raw text, without any meta-attributes such as click counts. A novel algorithm is ...
- 1Citation
MetricsTotal Citations1
- Article
Squeezing the ensemble pruning: faster and more accurate categorization for news portals
Cagri Toraman
Bilkent IR Group, Computer Engineering Department, Bilkent University, Ankara, Turkey
,Fazli Can
Bilkent IR Group, Computer Engineering Department, Bilkent University, Ankara, Turkey
ECIR'12: Proceedings of the 34th European conference on Advances in Information Retrieval•April 2012, pp 508-511• https://doi.org/10.1007/978-3-642-28997-2_52Recent studies show that ensemble pruning works as effective as traditional ensemble of classifiers (EoC). In this study, we analyze how ensemble pruning can improve text categorization efficiency in time-critical real-life applications such as news ...
- 0Citation
MetricsTotal Citations0
- Article
Ensemble pruning for text categorization based on data partitioning
Cagri Toraman
Bilkent Information Retrieval Group, Computer Engineering Department, Bilkent University, Ankara, Turkey
,Fazli Can
Bilkent Information Retrieval Group, Computer Engineering Department, Bilkent University, Ankara, Turkey
AIRS'11: Proceedings of the 7th Asia conference on Information Retrieval Technology•December 2011, pp 352-361• https://doi.org/10.1007/978-3-642-25631-8_32Ensemble methods can improve the effectiveness in text categorization. Due to computation cost of ensemble approaches there is a need for pruning ensembles. In this work we study ensemble pruning based on data partitioning. We use a ranked-based pruning ...
- 1Citation
MetricsTotal Citations1
Author Profile Pages
- Description: The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM bibliographic database, the Guide. Coverage of ACM publications is comprehensive from the 1950's. Coverage of other publishers generally starts in the mid 1980's. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community.
Please see the following 2007 Turing Award winners' profiles as examples: - History: Disambiguation of author names is of course required for precise identification of all the works, and only those works, by a unique individual. Of equal importance to ACM, author name normalization is also one critical prerequisite to building accurate citation and download statistics. For the past several years, ACM has worked to normalize author names, expand reference capture, and gather detailed usage statistics, all intended to provide the community with a robust set of publication metrics. The Author Profile Pages reveal the first result of these efforts.
- Normalization: ACM uses normalization algorithms to weigh several types of evidence for merging and splitting names.
These include:- co-authors: if we have two names and cannot disambiguate them based on name alone, then we see if they have a co-author in common. If so, this weighs towards the two names being the same person.
- affiliations: names in common with same affiliation weighs toward the two names being the same person.
- publication title: names in common whose works are published in same journal weighs toward the two names being the same person.
- keywords: names in common whose works address the same subject matter as determined from title and keywords, weigh toward being the same person.
The more conservative the merging algorithms, the more bits of evidence are required before a merge is made, resulting in greater precision but lower recall of works for a given Author Profile. Many bibliographic records have only author initials. Many names lack affiliations. With very common family names, typical in Asia, more liberal algorithms result in mistaken merges.
Automatic normalization of author names is not exact. Hence it is clear that manual intervention based on human knowledge is required to perfect algorithmic results. ACM is meeting this challenge, continuing to work to improve the automated merges by tweaking the weighting of the evidence in light of experience.
- Bibliometrics: In 1926, Alfred Lotka formulated his power law (known as Lotka's Law) describing the frequency of publication by authors in a given field. According to this bibliometric law of scientific productivity, only a very small percentage (~6%) of authors in a field will produce more than 10 articles while the majority (perhaps 60%) will have but a single article published. With ACM's first cut at author name normalization in place, the distribution of our authors with 1, 2, 3..n publications does not match Lotka's Law precisely, but neither is the distribution curve far off. For a definition of ACM's first set of publication statistics, see Bibliometrics
- Future Direction:
The initial release of the Author Edit Screen is open to anyone in the community with an ACM account, but it is limited to personal information. An author's photograph, a Home Page URL, and an email may be added, deleted or edited. Changes are reviewed before they are made available on the live site.
ACM will expand this edit facility to accommodate more types of data and facilitate ease of community participation with appropriate safeguards. In particular, authors or members of the community will be able to indicate works in their profile that do not belong there and merge others that do belong but are currently missing.
A direct search interface for Author Profiles will be built.
An institutional view of works emerging from their faculty and researchers will be provided along with a relevant set of metrics.
It is possible, too, that the Author Profile page may evolve to allow interested authors to upload unpublished professional materials to an area available for search and free educational use, but distinct from the ACM Digital Library proper. It is hard to predict what shape such an area for user-generated content may take, but it carries interesting potential for input from the community.
Bibliometrics
The ACM DL is a comprehensive repository of publications from the entire field of computing.
It is ACM's intention to make the derivation of any publication statistics it generates clear to the user.
- Average citations per article = The total Citation Count divided by the total Publication Count.
- Citation Count = cumulative total number of times all authored works by this author were cited by other works within ACM's bibliographic database. Almost all reference lists in articles published by ACM have been captured. References lists from other publishers are less well-represented in the database. Unresolved references are not included in the Citation Count. The Citation Count is citations TO any type of work, but the references counted are only FROM journal and proceedings articles. Reference lists from books, dissertations, and technical reports have not generally been captured in the database. (Citation Counts for individual works are displayed with the individual record listed on the Author Page.)
- Publication Count = all works of any genre within the universe of ACM's bibliographic database of computing literature of which this person was an author. Works where the person has role as editor, advisor, chair, etc. are listed on the page but are not part of the Publication Count.
- Publication Years = the span from the earliest year of publication on a work by this author to the most recent year of publication of a work by this author captured within the ACM bibliographic database of computing literature (The ACM Guide to Computing Literature, also known as "the Guide".
- Available for download = the total number of works by this author whose full texts may be downloaded from an ACM full-text article server. Downloads from external full-text sources linked to from within the ACM bibliographic space are not counted as 'available for download'.
- Average downloads per article = The total number of cumulative downloads divided by the number of articles (including multimedia objects) available for download from ACM's servers.
- Downloads (cumulative) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server since the downloads were first counted in May 2003. The counts displayed are updated monthly and are therefore 0-31 days behind the current date. Robotic activity is scrubbed from the download statistics.
- Downloads (12 months) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 12-month period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (12-month download counts for individual works are displayed with the individual record.)
- Downloads (6 weeks) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 6-week period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (6-week download counts for individual works are displayed with the individual record.)
ACM Author-Izer Service
Summary Description
ACM Author-Izer is a unique service that enables ACM authors to generate and post links on both their homepage and institutional repository for visitors to download the definitive version of their articles from the ACM Digital Library at no charge.
Downloads from these sites are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to definitive version of ACM articles should reduce user confusion over article versioning.
ACM Author-Izer also extends ACM’s reputation as an innovative “Green Path” publisher, making ACM one of the first publishers of scholarly works to offer this model to its authors.
To access ACM Author-Izer, authors need to establish a free ACM web account. Should authors change institutions or sites, they can utilize the new ACM service to disable old links and re-authorize new links for free downloads from a different site.
How ACM Author-Izer Works
Authors may post ACM Author-Izer links in their own bibliographies maintained on their website and their own institution’s repository. The links take visitors to your page directly to the definitive version of individual articles inside the ACM Digital Library to download these articles for free.
The Service can be applied to all the articles you have ever published with ACM.
Depending on your previous activities within the ACM DL, you may need to take up to three steps to use ACM Author-Izer.
For authors who do not have a free ACM Web Account:
- Go to the ACM DL http://dl.acm.org/ and click SIGN UP. Once your account is established, proceed to next step.
For authors who have an ACM web account, but have not edited their ACM Author Profile page:
- Sign in to your ACM web account and go to your Author Profile page. Click "Add personal information" and add photograph, homepage address, etc. Click ADD AUTHOR INFORMATION to submit change. Once you receive email notification that your changes were accepted, you may utilize ACM Author-izer.
For authors who have an account and have already edited their Profile Page:
- Sign in to your ACM web account, go to your Author Profile page in the Digital Library, look for the ACM Author-izer link below each ACM published article, and begin the authorization process. If you have published many ACM articles, you may find a batch Authorization process useful. It is labeled: "Export as: ACM Author-Izer Service"
ACM Author-Izer also provides code snippets for authors to display download and citation statistics for each “authorized” article on their personal pages. Downloads from these pages are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to the definitive version of ACM articles should reduce user confusion over article versioning.
Note: You still retain the right to post your author-prepared preprint versions on your home pages and in your institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library. But any download of your preprint versions will not be counted in ACM usage statistics. If you use these AUTHOR-IZER links instead, usage by visitors to your page will be recorded in the ACM Digital Library and displayed on your page.
FAQ
- Q. What is ACM Author-Izer?
A. ACM Author-Izer is a unique, link-based, self-archiving service that enables ACM authors to generate and post links on either their home page or institutional repository for visitors to download the definitive version of their articles for free.
- Q. What articles are eligible for ACM Author-Izer?
- A. ACM Author-Izer can be applied to all the articles authors have ever published with ACM. It is also available to authors who will have articles published in ACM publications in the future.
- Q. Are there any restrictions on authors to use this service?
- A. No. An author does not need to subscribe to the ACM Digital Library nor even be a member of ACM.
- Q. What are the requirements to use this service?
- A. To access ACM Author-Izer, authors need to have a free ACM web account, must have an ACM Author Profile page in the Digital Library, and must take ownership of their Author Profile page.
- Q. What is an ACM Author Profile Page?
- A. The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM Digital Library. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community. Please visit the ACM Author Profile documentation page for more background information on these pages.
- Q. How do I find my Author Profile page and take ownership?
- A. You will need to take the following steps:
- Create a free ACM Web Account
- Sign-In to the ACM Digital Library
- Find your Author Profile Page by searching the ACM Digital Library for your name
- Find the result you authored (where your author name is a clickable link)
- Click on your name to go to the Author Profile Page
- Click the "Add Personal Information" link on the Author Profile Page
- Wait for ACM review and approval; generally less than 24 hours
- Q. Why does my photo not appear?
- A. Make sure that the image you submit is in .jpg or .gif format and that the file name does not contain special characters
- Q. What if I cannot find the Add Personal Information function on my author page?
- A. The ACM account linked to your profile page is different than the one you are logged into. Please logout and login to the account associated with your Author Profile Page.
- Q. What happens if an author changes the location of his bibliography or moves to a new institution?
- A. Should authors change institutions or sites, they can utilize ACM Author-Izer to disable old links and re-authorize new links for free downloads from a new location.
- Q. What happens if an author provides a URL that redirects to the author’s personal bibliography page?
- A. The service will not provide a free download from the ACM Digital Library. Instead the person who uses that link will simply go to the Citation Page for that article in the ACM Digital Library where the article may be accessed under the usual subscription rules.
However, if the author provides the target page URL, any link that redirects to that target page will enable a free download from the Service.
- Q. What happens if the author’s bibliography lives on a page with several aliases?
- A. Only one alias will work, whichever one is registered as the page containing the author’s bibliography. ACM has no technical solution to this problem at this time.
- Q. Why should authors use ACM Author-Izer?
- A. ACM Author-Izer lets visitors to authors’ personal home pages download articles for no charge from the ACM Digital Library. It allows authors to dynamically display real-time download and citation statistics for each “authorized” article on their personal site.
- Q. Does ACM Author-Izer provide benefits for authors?
- A. Downloads of definitive articles via Author-Izer links on the authors’ personal web page are captured in official ACM statistics to more accurately reflect usage and impact measurements.
Authors who do not use ACM Author-Izer links will not have downloads from their local, personal bibliographies counted. They do, however, retain the existing right to post author-prepared preprint versions on their home pages or institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library.
- Q. How does ACM Author-Izer benefit the computing community?
- A. ACM Author-Izer expands the visibility and dissemination of the definitive version of ACM articles. It is based on ACM’s strong belief that the computing community should have the widest possible access to the definitive versions of scholarly literature. By linking authors’ personal bibliography with the ACM Digital Library, user confusion over article versioning should be reduced over time.
In making ACM Author-Izer a free service to both authors and visitors to their websites, ACM is emphasizing its continuing commitment to the interests of its authors and to the computing community in ways that are consistent with its existing subscription-based access model.
- Q. Why can’t I find my most recent publication in my ACM Author Profile Page?
- A. There is a time delay between publication and the process which associates that publication with an Author Profile Page. Right now, that process usually takes 4-8 weeks.
- Q. How does ACM Author-Izer expand ACM’s “Green Path” Access Policies?
- A. ACM Author-Izer extends the rights and permissions that authors retain even after copyright transfer to ACM, which has been among the “greenest” publishers. ACM enables its author community to retain a wide range of rights related to copyright and reuse of materials. They include:
- Posting rights that ensure free access to their work outside the ACM Digital Library and print publications
- Rights to reuse any portion of their work in new works that they may create
- Copyright to artistic images in ACM’s graphics-oriented publications that authors may want to exploit in commercial contexts
- All patent rights, which remain with the original owner