EVENT REPORT

Report on the 13th Workshop on Temporal Web
Analytics (TempWeb 2023) at WWW 2023
Marc Spaniol

Ricardo Baeza-Yates

Omar Alonso

University of Caen Normandy
FranceNortheastern University
USA

AmazonUSA

marc.spaniol@unicaen.fr

rbaeza@acm.org

oralonso@gmail.com

Abstract
TempWeb is an established Workshop (series) with a long-standing tradition as a co-locatedevent at The Web Conference. Considering the constantly evolving Web as a primaryobject of research, TempWeb provides a platform to present longitudinal studies on the
Web (structure), its contents, and its communities, etc. by aiming at the investigation of
infrastructures, scalable methods, and innovative software for aggregating, querying, andanalyzing heterogeneous data at Web scale. Since longitudinal aspects in Web analytics
is becoming more and more inter- and transdiciplinary relevant for analysts from various
domains, the studies, tools, and demonstrations are not only limited to computer science, butalso open to sociology, marketing, environmental studies, politics, etc., to name just a few.
As such, TempWeb has developed as a forum for a community from academia and industry
covering temporal Web analytics at all levels of granularity and across various disciplines.
Date: 1 May 2023.
Website: http://temporalweb.net/.

1

Introduction

TempWeb 2023 was the thirteenth event in its workshop series and took place co-located on 1st
May 2023 in conjunction with The Web Conference WWW 20231 . After three tough years in“quarantine”, TempWeb 2023 and WWW 2023 were the first editions in a post pandemic era andintended to be held primarily as onsite events, this time in Austin, TX, USA. However, due toorganizational constraints both events took place in a partial hybrid mode with an emphasis ononsite participation.
The focus of TempWeb and the topics addressed are a “natural” match with The Web Conference.
With digital content born almost two decades ago, the need for a more systematic exploitation of
our digital cultural heritage as well as new analysis techniques, becomes evident. Hence, TempWeb
is an ideal venue to exchange knowledge about temporal analytics at a Web scale with experts
from science and industry. Further workshop details can be found on the workshop homepage2 .
12

https://www2023.thewebconf.org/
http://temporalweb.net/

ACM SIGIR Forum

1

Vol. 57 No. 2 – December 2023

The program of TempWeb 2023 was organized as a full day workshop in five sessions:
Session 1: Workshop Welcome and Introduction
Session 2: Temporal Social Media
Session 3: Communities & Time
Session 4: Events and the Temporal Dimension
Session 5: Open Discussion and Final Remarks
Further information about the program of the workshop is available at the conference website3 .

2

Workshop Objectives and Topics

The objective of TempWeb was to provide a venue for researchers of all domains (IE/IR, Web
mining, etc.) where the temporal dimension opens an entirely new range of possibilities andchallenges. The workshop’s ambition was to keep shaping a community of interest on researchissues resulting from the introduction of the time dimension in web mining and analysis. The
maturity of the Web as well as the emergence of large-scale repositories of Web content made thisvery timely and as a result, a growing number of research projects and services were emerging thathave this focus in common. Having a dedicated workshop helped to take a rich and cross-domain
approach to this continuous research with a strong focus on the temporal dimension.
TempWeb focused on investigating infrastructures, scalable methods, and innovative software
for aggregating, querying, and analyzing heterogeneous data at Web scale. Emphasis was given
to temporal data analysis along the time dimension for Web data that had been collected overextended time periods. A major challenge in this regard was the sheer size of the data it exposed
and the ability to make sense of it in a useful and meaningful manner for its users. As such,longitudinal aspects in Web content analysis became relevant for analysts from various domains,
including, but not limited to sociology, marketing, environmental studies, politics, etc. Studies inthis context ranged from “low-level” structural network log analysis over time, up to “high-level”
entity-level Web content analytics and terminology evolution. While both before mentioned aspects
represent the extremes of the spectrum, they have one thing in common: Web scale data analytics
needed and still needs to develop infrastructures and extended analytical tools in order to make useof that data. To this end, workshop topics of TempWeb therefore included, but were not limited
to the following:• Web scale data analytics• Temporal Web analytics• Distributed data analytics• Web science• Web dynamics• Data quality metrics• Web spam evolution• Content evolution on the Web• Systematic exploitation of Web archives
3• Large scale data storage• Large scale data processing• Time aware Web archiving• Data aggregation• Web trends• Topic mining• Terminology evolution• Community detection and evolution

https://archives.iw3c2.org/www2023/program/detailed-program/

ACM SIGIR Forum2

Vol. 57 No. 2 – December 2023

3

Workshop Contributions

For its thirteenth edition, TempWeb accepted eight very positively reviewed submissions fororal presentation (acceptance rate of ∼70%) [Spaniol et al., 2023a]. The high quality of thesubmissions and the frequent contributors to TempWeb can be interpreted, as indicators of anevolving community. It shows a clear sign of a positive dynamic in the study of time in the scopeof the Web and evidence of the relevance of this effort.
This edition was started with a Welcome and Introduction session by the Workshop organizers.
The statements were intended to outline the workshop objectives and to introduce the agenda
for the upcoming day. The workshop was decomposed into three technical sessions and an open
discussion session concluding the workshop. In order to give a brief overview on the contents
presented at TempWeb 2023, we summarize the key contributions of the accepted papers in thechronological order of their presentation [Spaniol et al., 2023b].
First, Farnoosh Hashemi, Ali Behrouz and Milad Rezaei Hajidehi presented CS-TGN: Community Search via Temporal Graph Neural Networks [Hashemi et al., 2023]. Particularly, they
investigated community search through identification of densely connected subgraph containing
query nodes. To this end, they introduced a query-driven temporal graph convolutional networkthat overcomes shortcomings of adopting pre-defined subgraph patterns and solely incorporating
the aggregation of disjoint structural information for quality assessment. As a result, CS-TGN
is capable of identifying community structures by intertwining local structures and global graphsnapshots at each time point in combination with contextual attention in order to update theembeddings over time.
Next, Ke Li, Zhiwen Yu, Ying Zhang and Bin Guo addressed the Impact of COVID-19 Pandemic
on Cultural Products Interests [Li et al., 2023]. In contrast to user-driven surveys, their approachaims at exploiting user-oriented data on the Web. To this end, they conducted a study over searchinterests in various countries and across a multitude of domains. The results highlight a strong
correlation in interests and mobility reduction. Particularly, an increase of dematerialized media
was recognizable.
The societal thread of influence campaigns was then highlighted in Detecting the Hidden
Dynamics of State-Backed Influencers Using Temporal Correlations by Keeley Erhardt and Dina
Albassam [Erhardt and Albassam, 2023]. While existing approaches are mostly constrained totarget orchestrated campaigns, the authors presented a novel generative model that allows to reveal
coordinated inauthentic activity of individual social media accounts. To this end, their model
describes the interactions between networked Markov chains.
In The Age of Snippet Programming: Towards Understanding Developers Communities in
Stack Overflow and Reddit, Alessia Antelmi, Gennaro Cordasco, Daniele De Vinco and Carmine
Spagnuolo analyze the importance of community contribution-based question-and-answer (Q&A)
platforms as an information source of coding related knowledge exchange [Antelmi et al., 2023]. To
this end, they conducted longitudinal study on the posting activities of users and their high-orderinteraction patterns abstracted via hypergraphs. Their results reveal significant differences between
Stack Overflow and Reddit. In particular, they highlight a trend towards highly community-friendly
platforms, e.g., Reddit.
Subsequently, Behrooz Mansouri, Ricardo Campos and Adam Jatowt introduced a novel
approach Towards Timeline Generation with Abstract Meaning Representation [Mansouri et al.,
ACM SIGIR Forum

3

Vol. 57 No. 2 – December 2023

2023]. In their paper, the authors employ a graphical representation of the text where the nodes
are semantic concepts and the edges denote relationships between concepts. To this end, sentences
are selected that contain the highest number of named-entities and are then sorted based on a
combined score of Inverse Document Frequency (IDF) of graph nodes and a keyword extraction
method. Experiments on A COVID-19 data set showed the viability of the approach.
In Gone, Gone, but Not Really, and Gone, But Not forgotten: A Typology of Website Recoverability Brenda Reyes Ayala studies the recoverability of Web pages [Ayala, 2023]. To this end,
four Web archive collections were used in order to analyze the content and evolution of previously
thought to be lost Web pages. This resulted in three types of lost contents: not recoverable, fully
recoverable and partially recoverable. Based on the before introduced categories, Web archivists
were supported in finding those contents that were previously considered to be lost yielding to amore complete Web archive.
A novel approach of reliable discovering new content from Web sites was introduced by Peter
Schulam and Ion Muslea in Improving the Exploration/Exploitation Trade-Off in Web Content
Discovery [Schulam and Muslea, 2023]. They observed that SOTA implementations employ
probabilistic methods that result in a sub-optimal balancing of exploration and exploitation. In
order to overcome this deficit the developed a new crawler called Thompson, named after samplerthat drives its refresh decisions. In experiments they were then able to show that their approach
outperforms the SOA in various dimensions due to a better modeling of the action space.
Finally, Aparna Varde, Gerard de Melo and Boxiang Dong presented their research on Temporal
Ordinance Mining for Event-Driven Social Media Reaction Analytics [Varde et al., 2023]. For that
purpose, they proposed a research agenda enabling novel forms of temporally-driven ordinancecontent analysis and Web question answering. In combination with an ongoing social media
analysis this will ultimately enable historical ordinance mining. As a result, the overall process
will become more transparent for both legislators and the broader public.

4

Conclusion and Future Directions

As in previous years, the TempWeb 2023 was highly interactive. Many discussions emerged fromthe presented papers and were brought over to the panel. Not surprisingly, the many facets of
temporal Web analytics became evident and showed the importance of their investigation at avenue like TempWeb. Participants were very engaged in the discussions and asked many times fora continuation of running the workshop, which shows a continuous interest on the topic.
Based on the very positive feeddack, a proposal for TempWeb 2024 was submitted and later
accepted for the upcoming edition of The Web Conference. Thus, TempWeb 2024 will take place
as an in presence event to be held on May 14 in Singapore. In addition, a special issue on “The
Temporal Web: Investigating Time and the Temporal Dimension” has been released at ACM
Transactions on The Web (cf. the CfP4 for details).
4

https://dl.acm.org/pb-assets/static_journal_pages/tweb/pdf/TWEB-CfP-Temporal-Web.pdf

ACM SIGIR Forum

4

Vol. 57 No. 2 – December 2023

Acknowledgements
TempWeb thanks the authors of submitted papers for their efforts, and all workshop attendees.
TempWeb 2023 was jointly organized by University of Caen Normandy (Caen, France), Northeastern University (Silicon Valley, CA, USA) and Amazon, Santa Clara, CA, USA. We also wish to
express our particular thanks to our program committee members:• Eytan Adar (University of Michigan, USA)
• Srikanta Bedathur (IIT Delhi, India)• Andras A. Benczur (Hungarian Academy of Science)• Behrooz Mansouri (Rochester Institute of Technology, USA)
• Ricardo Campos (Polytechnic Institute of Tomar)• Govind (Amazon, India)• Adam Jatowt (University of Innsbruck, Austria)• Nattiya Kanhabua (Upwork, Bangkok, Thailand)• Scott Kirkpatrick (Hebrew University Jerusalem, Israel)• Amit Kumar (Tarento Technologies Pvt Limited, India)• Frank McCown (Harding University, USA)
• Michael Nelson (Old Dominion University, USA)
• Nikos Ntarmos (Huawei Technologies R&D, UK)• Kjetil Nørvåg (Norwegian University of Science and Technology, Norway)• Thomas Risse (University Library Johann Christian Senckenberg, Germany)• Andreas Spitz (University of Konstanz, Germany)• Jannik Strötgen (Bosch Center for Artificial Intelligence, Germany)• Torsten Suel (NYU Polytechnic, USA)
• Masashi Toyoda (Tokyo University, Japan)• Gerhard Weikum (Max-Planck-Institut für Informatik, Germany)
Last but not least, we would like to thank the organizers of WWW2023 for hosting the workshops
and providing the online meeting facilities.

References
Alessia Antelmi, Gennaro Cordasco, Daniele De Vinco, and Carmine Spagnuolo. The Age of Snippet
Programming: Toward Understanding Developer Communities in Stack Overflow and Reddit.
In Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos Castillo, and Geert-Jan Houben,
editors, Companion Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX,
USA, 30 April 2023 - 4 May 2023, pages 1218–1224. ACM, 2023. doi: 10.1145/3543873.3587673.
URL https://doi.org/10.1145/3543873.3587673.
Brenda Reyes Ayala. Gone, Gone, but Not Really, and Gone, But Not forgotten: A Typology ofWebsite Recoverability. In Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos Castillo,
and Geert-Jan Houben, editors, Companion Proceedings of the ACM Web Conference 2023,
ACM SIGIR Forum

5

Vol. 57 No. 2 – December 2023

WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023, pages 1208–1213. ACM, 2023. doi:
10.1145/3543873.3587671. URL https://doi.org/10.1145/3543873.3587671.
Keeley Erhardt and Dina Albassam. Detecting the Hidden Dynamics of Networked Actors Using
Temporal Correlations. In Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos Castillo,
and Geert-Jan Houben, editors, Companion Proceedings of the ACM Web Conference 2023,
WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023, pages 1214–1217. ACM, 2023. doi:
10.1145/3543873.3587672. URL https://doi.org/10.1145/3543873.3587672.
Farnoosh Hashemi, Ali Behrouz, and Milad Rezaei Hajidehi. CS-TGN: Community Search via
Temporal Graph Neural Networks. In Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos
Castillo, and Geert-Jan Houben, editors, Companion Proceedings of the ACM Web Conference
2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023, pages 1196–1203. ACM,
2023. doi: 10.1145/3543873.3587654. URL https://doi.org/10.1145/3543873.3587654.
Ke Li, Zhiwen Yu, Ying Zhang, and Bin Guo. Impact of COVID-19 Pandemic on Cultural
Products Interests. In Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos Castillo,
and Geert-Jan Houben, editors, Companion Proceedings of the ACM Web Conference 2023,
WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023, pages 1190–1195. ACM, 2023. doi:
10.1145/3543873.3587594. URL https://doi.org/10.1145/3543873.3587594.
Behrooz Mansouri, Ricardo Campos, and Adam Jatowt. Towards Timeline Generation with
Abstract Meaning Representation. In Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos
Castillo, and Geert-Jan Houben, editors, Companion Proceedings of the ACM Web Conference
2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023, pages 1204–1207. ACM,
2023. doi: 10.1145/3543873.3587670. URL https://doi.org/10.1145/3543873.3587670.
Peter Schulam and Ion Muslea. Improving the Exploration/Exploitation Trade-Off in Web
Content Discovery. In Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos Castillo,
and Geert-Jan Houben, editors, Companion Proceedings of the ACM Web Conference 2023,
WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023, pages 1183–1189. ACM, 2023. doi:
10.1145/3543873.3587574. URL https://doi.org/10.1145/3543873.3587574.
Marc Spaniol, Ricardo Baeza-Yates, and Omar Alonso, editors. Proceedings of the 13th Temporal
Web Analytics Workshop (TempWeb 2023), Austin, TX, USA, 30 April 2023 - 4 May 2023,
2023a. ACM. ISBN 978-1-4503-9130-6.
Marc Spaniol, Ricardo Baeza-Yates, and Omar Alonso. 13th Temporal Web Analytics Workshop(TempWeb) Overview. In Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos Castillo,
and Geert-Jan Houben, editors, Companion Proceedings of the ACM Web Conference 2023,
WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023, page 1182. ACM, 2023b. doi:
10.1145/3543873.3589742. URL https://doi.org/10.1145/3543873.3589742.
Aparna S. Varde, Gerard de Melo, and Boxiang Dong. Temporal Ordinance Mining for Event-Driven
Social Media Reaction Analytics. In Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos
Castillo, and Geert-Jan Houben, editors, Companion Proceedings of the ACM Web Conference
2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023, pages 1225–1227. ACM,
2023. doi: 10.1145/3543873.3587674. URL https://doi.org/10.1145/3543873.3587674.
ACM SIGIR Forum

6

Vol. 57 No. 2 – December 2023