How Do Ideas Flow around SIGMM Conferences?

Author: Lexing Xie
Affiliation: Research School of Computer Science at the Australian National University

 

The ACM Multimedia conference just celebrated its quarter century in October 2017. This is a great opportunity to reflect on the intellectual influence of the conference, and the SIGMM community in general.

The progress on big scholarly data allows us to make this task analytical. I download a data dump from  Microsoft Academic Graph (MAG) in February 2016. I find all papers from ACM Multimedia (MM), the SIGMM flagship conference — there are 4,346 publication entries from 1993 to 2015. I then search the entire MAG for: (1) any paper that appears in the reference list of these MM papers – 35,829 entries across 1,560 publication venues (including both journals and conferences), with an average of 8.24 per paper; (2) any paper that cites any of these MM papers – 46826 citations from 1694 publication venues, with an average of 10.77 citations per paper.

This data allows us to profile the incoming (references) and outgoing (citations) influence in the community in detail. In this article, we highlight two questions below.

Where are the intellectual influences of the SIGMM community coming from, and going to?

If you have been publishing in, and going to SIGMM conference(s) for a while, you may wonder where the ideas presented today would have its influence after 5, 10, 20 years? You may also wonder if the ideas cross over to other fields and disciplines, and which stay and flourish within the SIGMM community. You may also wonder whether the influence flow has changed since you entered the community, 3, 5, 10, or 20+ years ago.

If you are new to SIGMM, you may wonder what this community’s intellectual heritage is. For new students or researchers who recently entered this area, you may wonder what other publication venues are you likely to find work relevant to multimedia.

Figure 1. The citation flow for ACM Multimedia (1993-2015). Summary of incoming vs outgoing citations to the top 25 venues in either direction. Node colors: ratio of citations (outgoing ideas, red) vs references (incoming ideas, blue). Node sizes: amount of total citation+references in either direction. Thickness of blue edges are scaled by the number of references going to a given venue; thickness of red edges are scaled by the number of citations coming from a given venue. Nodes are sorted left-to-right by the ratio of incoming vs outgoing citations to this conference.

Figure 1. The citation flow for ACM Multimedia (1993-2015). Summary of incoming vs outgoing citations to the top 25 venues in either direction. Node colors: ratio of citations (outgoing ideas, red) vs references (incoming ideas, blue). Node sizes: amount of total citation+references in either direction. Thickness of blue edges are scaled by the number of references going to a given venue; thickness of red edges are scaled by the number of citations coming from a given venue. Nodes are sorted left-to-right by the ratio of incoming vs outgoing citations to this conference.

A summary of this information is found in the “citation flower” graph above, summarising the incoming and outgoing influence since the inception of ACM MM (1993-2015).

On the right of the “citation flower” we can see venues that have had more influence in MM than otherwise, these include computer vision and pattern recognition (CVPR, ICCV, ECCV, T-PAMI, IJCV), machine learning (NIPS, JMLR, ICML), networking and systems (INFOCOM), information retrieval (SIGIR), human-computer interaction (CHI) as well as related journals (IEEE Multimedia). The diversity of incoming influence is part of the SIGMM identity, as the community has always been a place where ideas from disparate areas meet and generate interesting solutions to problems as well as generating new challenges. As indicated by the break down over time (on a separate page), the incoming influence of CVPR is increasing, and that of IEEE Trans. Circuits Systems on Video Technology is decreasing — this is consistent with video encoding technology maturing over the last two decades, and computer vision being fast-evolving currently.

On the left of the “citation flower”, we can see that ACM MM has been a major influencer for a variety of multimedia venues — from conferences (ICME, MIR, ICMR, CIVR) to journals (Multimedia Tools and Applications, IEEE Trans. Multimedia), to journals in related areas (IEEE Trans. On Knowledge Discovery and Engineering).

How many papers are remembered in the collective memory of the academic community and for how long?

Or, as a heated post-conference beer conversation may put it: are 80% of the papers forgotten in 2 years? Spoiler alert: no, for most conferences we looked at; but about 20% tend not be cited at all.

Figure 2. Fraction of ACM MM papers that are cited at least once more than X years after they are published, with a linear regression overlay.

Figure 2. Fraction of ACM MM papers that are cited at least once more than X years after they are published, with a linear regression overlay.

In Figure 2, we see a typical linear decline of the fraction of papers being cited. For example, 53% of papers have at least one citation after being published for 10 years. There are multiple factors that affect the shape of this citation survival graph, such as the size of this research community, the turnover rate of ideas (fast-moving or slow-moving), the perceived quality of publications, and others. See here for a number of different survival curves in different research communities.

What about the newer, and more specialised SIGMM conferences?

Figure 3 and Figure 4 show the citation flowers for ICMR and MMSys, both conferences have had five years of publication data in MAG. We can see that both conferences are well-embedded among the SIGMM and related venues (ACM Multimedia, IEEE Trans. Multimedia), both have strong influence from the computer vision community including T-PAMI, CVPR and ICCV. The sub-community specific influences are coming from WWW, ICML NIPS for ICMR; and INFOCOM, SIGMETRICS, SIGMAR for MMSys. In terms of out-going influence, MMSys influences venues in networking (ICC, CoNEXT), and ICMR influences Information Science and MMSys.

Figure 3. The citation flow for ICMR (2011-2015). See Figure 1 caption for the meaning of node/edge colors and sizes.

Figure 3. The citation flow for ICMR (2011-2015). See Figure 1 caption for the meaning of node/edge colors and sizes.

Figure 4. The citation flow for MMSys (2011-2015). See Figure 1 caption for the meaning of node/edge colors and sizes.

Figure 4. The citation flow for MMSys (2011-2015). See Figure 1 caption for the meaning of node/edge colors and sizes.

Overall, this case study shows the truly multi-disciplinary nature of SIGMM, the community should continue the tradition of fusing ideas and strive to increase its influence in other communities.  

I hope you find these analyzes and observations somewhat useful, and I would love to hear comments and suggestions from the community.  Of course, the data is not perfect, and there is a lot more to do. The project overview page [1] contains details about data processing and several known issues, software for this analysis and visualisation are also released publicly [2].

Acknowledgements

I thank Alan Smeaton and Pablo Cesar for encouraging this post and many helpful editing suggestions. I also thank Microsoft Academic for making data available.

References

[1] Visualizing Citation Patterns of Computer Science Conferences, Lexing Xie, Aug 2016,  http://cm.cecs.anu.edu.au/post/citation_vis/

[2] Repository for analyzing citation flow https://github.com/lexingxie/academic-graph

 

Bookmark the permalink.