Competition Dynamics in the Meme Ecosystem
CCompetition Dynamics in the Meme Ecosystem
Trenton Ford, Rachel Krohn, and Tim WeningerDepartment of Computer Science and EngineeringUniversity of Notre Dame { tford5, rkrohn, tweninger } @nd.edu Abstract
The creation and sharing of memes is a common modality ofonline social interactions. The goal of the present work is tobetter understand the collective dynamics of memes in this ac-celerating and competitive environment. By taking an ecolog-ical perspective and tracking the meme-text from 352 popularmemes over the entirety of Reddit, we are able to show that thefrequency of memes has scaled almost exactly with the totalamount of content created over the past decade. This meansthat as more data is posted, an equal proportion of memesare posted. One consequence of limited human attention inthe face of a growing number of memes is that the diversityof these memes has decreased at the community level, albeitslightly, in the same period. Another consequence is that theaverage lifespan of a meme has decreased dramatically, whichis further evidence of an increase in competition and a decreas-ing collective attention span.
Introduction
With the rise of social media platforms, the cost historicallyassociated with producing and consuming information has de-creased to unprecedented levels; users and organizations caneasily share their thoughts, stories, and others’ content withdiverse and widespread audiences with very little effort. Dueto the ease of production, the volume of content produced hasincreased to the point that any individual user can only seea small portion of what is available. The reduction in con-tent production cost and increase in availability has induceda change in scarcity dynamics: from content scarcity to con-sumer scarcity [30]. This shift in scarcity has birthed new re-search areas to help users see relevant content – such as rec-ommender systems – as part of the broader attention econ-omy [27].The attention economy seeks to explain the allocation ofcognitive resources in the creation and consumption of infor-mation. Though this concept existed long before the advent ofsocial media [29], recent work has focused on how this modelgoverns the dynamics of content consumers and curators inthe socio-digital space [8, 9]. The main focus has been on theconsumption of information [34, 36, 12], but others focus onthe production and curation of information [4, 17, 10, 28, 13]. Figure 1: Meme image with text meant to be condescendingto the subject. The text of this meme and others like it arefrequently used without the image in humorous or sarcasticcontexts.One of the primary questions at the center of online social me-dia is this: how does the limited attention of users shape theinformation landscape?One particularly compelling subset of the information land-scape is the production and resharing of compelling memes,which are short phrases and images. For example, the image inFigure 1 is a meme with text that is meant to be condescend-ing to the subject; oftentimes, the text of the meme is indepen-dent of its image and is written in plaintext in comments andtweets. The dynamics of these viral messages are not well un-derstood despite widespread attempts to predict and simulatetheir spread or popularity [3, 1]. Yet this narrow subset of theinformation landscape is an increasingly visible and influentialcommunication mode with exciting properties. A meme’s pop-ularity can be quantified by how many times it is reproducedor shared, how long it stays relevant, and how many times it ismutated – in the case of meme images.Intuition about how memes are created, transmitted, con-sumed, or mutated are often derived from their associationwith genes and the process of gene evolution [5] and morerecently, memes have been considered through the lens of epi-demiology and disease transmission [33, 16]. Indeed, its ety-mology is a portmanteau of mind+gene, which begs the ques-tion: rather than continuing the economic analogy, are memesbetter situated in the realm of ecology ? And if so, what kind ofunderstanding can be gleaned from this perspective?In the present work, we derive findings about competition1 a r X i v : . [ c s . S I] F e b nd diffusion of information from the ecological perspective.There are many compelling examples that motivate this per-spective. Foremost is the concept of competition , which is adriving force in genealogical, economic, epidemiological, andecology fields [22]. In analogical terms, the goal of competingmemes is their continued existence within the minds and com-munication patterns of people. Survival , therefore, follows as anatural extension of competition, which presumes that memesare designed with survival in mind [35, 17].The differences between the ecological perspective and oth-ers are nuanced. Fundamentally, each perspective offers aunique interpretation of information dynamics. For example,within the economics perspective, human behavior ( e.g. , at-tention) is the primary focus, and memes just one of manypossible factors. From an epidemiological perspective, memesare treated as a contagion ( e.g. , a virus), but epidemiologi-cal models typically do not consider landscapes with multi-ple viruses and their interactions. The genealogical perspec-tive treats memes as genes and explores gene-gene interac-tions, but the gene perspective does not natively consider gene-environment interactions.In taking the ecological perspective, we consider a memeto be a single species existing within the same environmentor habitat. The ecological perspective shifts the focus awayfrom the human users and back to the memes and the environ-ments they exist within – wherein memes seek both longevityand a large population, competing for limited environmentalresources – human attention.Within the perspective of the meme ecology , we ask the fol-lowing research questions:RQ1: How does the collective user attention scale? Domore users permit a larger or smaller number ofmemes?RQ2: How do memes compete for attention? How does theintroduction of a new meme impact the ecosystem ofexisting memes?RQ3: How have the dynamics of collective attentionchanged over time?In summary, by using well-known metrics and conceptsfrom ecology, we perform an ecological analysis of the dy-namics of text-memes on Reddit. The results of this analysisand the behavior they suggest are compelling and strongly sup-port the case for the ecology of memes. We find that memescomprise a relatively constant fraction of all activity on theplatform, even as social media increases in popularity. Thissuggests that as more memes are created their lifecycle dura-tion becomes shorter, which further suggests that the collectivehuman attention span on social media is decreasing.Although the current work focuses on short, frequently re-peated texts, i.e. , memes, we further hypothesize that our find-ings are likely to apply to a number of other communicationmodalities like image-memes and hashtags.
Tokens Count Examples
Table 1: Meme dataset consists of 352 text memes, ranging inlength from 1 to 8 tokens. Some memes reference current pop-culture events, while others seem unconnected to trends of thetime. · A c t i v i t y total posts total comments (A) · Time (Years) B ( t ) Background Language Model (B)
Figure 2: (A) Stacked line plot representation of Reddit con-tributions between 2010 and 2020. The lower (orange) re-gion shows the number of posts per month; the upper (blue)region shows the number of comments per month. (B) Theunigram background model is used to compute normalizedmeme-frequencies. This background behavior closely mirrorsthe growth of Reddit, but is one order of magnitude larger.
Data Collection
Using a comprehensive dataset of the 352 most popular memesfrom KnowYourMeme.com, we identified their individual oc-currences on Reddit. The memes were selected from the Con-firmed category on KnowYourMeme, and include text-basedmemes that ranged from 250 thousand to 13 million pageviews each. Note that the tracking of rapidly-evolving im-age templates is outside the scope of the present work; there-fore, image-memes are not included in this analysis. Extendedmeme text ( e.g. , copypasta ) is truncated to include only the 8-token prefix. The final set contains meme-phrases that rangein length from 1 to 8 word tokens as shown in Table 1. Addi-tionally, we collected all posts and comments from Jan. 2010to Jan. 2020; the number of monthly posts and comments isplotted in Figure 2.2he questions raised in the present work are considered hu-man subjects research, and relevant ethical considerations arepresent. We sought and received research approval from theInstitution Review Board of redacted . Collective Attention to Memes is Station-ary
Previous work has shown that innovation and technologicaldevelopment is accelerating. Moore’s Law is one exampleof this phenomenon where a compounding increase in cir-cuit density has led to remarkable increases in computationalpower [26]; similar effects have been shown in genome se-quencing [21] and telecommunications bandwidth [6]. In on-line social systems, the early empirical evidence suggests thata similar pattern exists: that social innovations are accelerat-ing [18, 24, 14, 25].This is the basis for
RQ1 : How does collective user atten-tion of memes scale? Does the presence of larger groups resultin super-scaling effects like those found in population densi-ties [23] and software development [32] where collections ofindividuals produce more than the sum of their parts?At first glance, Figure 2 appears to show that our data sup-ports these claims: more posts, comments, and memes are be-ing made at an accelerating pace year over year. But how muchattention is paid to individual memes? To answer this question,we first need to measure collective attention.
Measuring Collective Attention
Because we cannot collect the number of users who viewedor thought about a particular meme, instead, we estimate thecollective attention for each meme by the number of times itappears, i.e. , its frequency. So our first task is to extract thedaily frequency F m ( t ) of each meme, such that F m ( t ) is thefrequency of meme m on day t . Given the scale variance ofsocial media sites, simply counting tokens would be insuffi-cient to fully determine whether memes are truly increasing inprevalence or if their frequency increases mirror the increasein content that Reddit has experienced overall. In order to pro-duce as accurate assessment of the meme ecology, we need tocarefully normalize the frequency of meme occurrences.To do this, we constructed a set of 5000 randomly selectedwords from Reddit to serve as a background language model.Then, for each day, we count the number of occurrences ofeach token in the background set, such that B ( t ) gives thebackground sum of all 5000 words on day t . As the numberof posts and comments on Reddit grows over time, so too dothe occurrences of the background set. As seen in Figure 2, thebackground growth closely mirrors the growth of Reddit.Likewise, we expect the number of meme occurrences toincrease at a similar rate. In order to control for the growth ofReddit over time we compute the normalized meme-frequency for each meme ˆ F m ( t ) = F m ( t ) /B ( t ) .Figure 3 illustrates the mean average normalized meme-frequency along with its 95% confidence interval from 2010 to · − Time (Years) M ean N o r m a li z ed M e m e - F r equen cy Figure 3: Average normalized meme-frequency from 2010–2020 and 95% confidence interval (shaded region). Light greylines show the individual normalized meme-frequency for arandom 10% sample of individual memes. Overall, meme oc-currence has remained consistent over the past decade (Pear-son R = +0.03 , p -value < ).2020. A selection of individual memes are also plotted in lightgrey. We find that the occurrence of memes remains remark-ably consistent when controlled for Reddit’s overall activity,even as the occurrence of individual memes varies widely.Correlation analysis finds almost no association between timeand the normalized meme-frequency (Pearson R = +0.03 , p -value < Competition Among Memes
The prevalence of individual memes rises and falls over time.Popularity is fleeting, but as a meme dies out, another alwaysseems to rise to take its place. The ebb and flow of what isor is no longer popular has long been studied as the diffusionof innovations [7]. The study of the production and evolutionof innovations ( e.g. , new ideas, behaviors, memes, and otherinformation patterns) has recently become particularly com-3
010 2012 2014 2016 2018 2020 · Time (Years) S ub r edd i t s − x + 0.40 A v e r age S i m p s on D i v e r s i t y I nde x Figure 4: Average Simpson’s Diversity Index across subred-dits, and number of subreddits, over time. Meme diversity onReddit is decreasing (Pearson R = − , p -value < )with a small slope (0.04% per month) despite an increase inthe number of subreddits containing memes.pelling because of the availability of vast amounts of humanbehavior happening through online social platforms.The dynamic behavior of memes, in particular, suggeststhat these ideas exist in constant competition with one an-other. The competition among memes is not unlike competi-tion observed in markets, where innovations eventually replaceoutdated products, or ecological systems, where competitionamong individuals in a group exerts a selective pressure thatrewards certain genetic innovations.Continuing the ecological analogy, one way to assess thehealth of an ecological system is to examine the diversity ofthe species living within the system. From this perspective,the ecology of a social media environment ought to have sev-eral different memes simultaneously appearing in abundance.This leads us to RQ2 : How do memes compete for attention?Specifically, as Reddit grows and new memes are introduced,does the overall diversity increase or decrease?One way to measure the diversity of an ecological systemis with Simpson’s Diversity Index ( D ) [11]. This index takesinto account both the number of species present, as well as thepopulation of each species. It is formally defined as: D = 1 − (cid:80) Ri =1 n i ( n i − N ( N − (1)Where R is the total number of species in a community (num-bered through R ), N is the total number of organisms, and n i is the number of individuals belonging to species i . For ourpurposes, we consider a subreddit to be a community, eachmeme as its own species, and each meme occurrence as aspecies entity. D ranges from 0 to 1, where 0 indicates no di-versity and 1 indicates infinite diversity.We compute the Simpson’s Diversity Index for each sub-reddit in each month. We then compute the average monthlySimpson Diversity across all subreddits, resulting in a monthlyaverage diversity of Reddit at the community level. Figure 4shows the average diversity and 95% confidence intervals overtime. Overall, the diversity of Reddit communities appears to be decreasing at a small (0.48% per year) but steady rate (Pear-son R = − , p -value < Innovative Communities
Ecological research focuses on the environments in whichspecies exist; the communities and biomes that spawn new species are often the focus of study because they can host ex-otic species along with high levels of species diversity [19].The same is true in social media, where the study of the cre-ation and diffusion of innovations within social environmentsis a central topic of research. The detection and analysis ofhighly innovative communities are of great interest in this lineof work [15]. As a direct consequence of our findings in RQ2we further ask: Are there certain communities that consistentlyintroduce new memes? These meme-nurseries are the placeswhere many new linguistic and cultural innovations are bornand cultivated. We further ask: do these innovative communi-ties persist over time, or is their high-innovation only tempo-rary?To answer these questions, we first define a meme entryevent as the first time that a meme is used within the Redditecosystem. The subreddit in which it first appears is definedas the landing space or beachhead for the new meme. Froman ecological perspective, a new meme is analogous to newspecies, and subreddits are the host habitats. Because Reddititself exists within the even larger environment of the socialinternet, tracing the true spread of a meme between specificcommunities is intractable. For this reason, it is necessary toconsider that a single meme may have multiple beachheadswithin Reddit.Under these circumstances, we elect to rank subredditsbased on the order in which a meme first appears; this method-ology reasonably controls for the uncertainty about whichcommunity was first, second, etc., to articulate the innovation.We constrict our analysis to the first 1000 subreddits to useeach meme. Based on this ordering, we compute the mean re-ciprocal rank (MRR) of each community with respect to eachof our 352 memes. These MRR values consider the rank foreach subreddit for each year in the dataset. The top 10 mostinnovative subreddits in the odd-numbered years (due to spaceconstraints) are given in Table 2It is clear that certain subreddits contribute a disproportion-ate number of new memes to Reddit. The colors in Table 2 rep-resent the top 10 subreddits from all 10 years combined. It isunclear why these subreddits are more innovative than others,but there may be conditions within these particular communi-ties that increase their ability to produce viral content moreregularly than others. No matter the cause, optimal meme-4 ank 2011 2013 2015 2017 2019
Table 2: Top 10 most innovative subreddits by year. Colored subreddit names show the top 10 most innovative subreddits from2010 to 2020 in aggregate.nursery conditions appear to be transient, as subreddits can behighly innovative one year, and not the next.There are a few conclusions to be drawn here. Early in Red-dit’s history, massive and highly contributive subreddits – like/r/reddit.com and /r/AskReddit – were the primary beachheadsfor new memes. However, as years progressed the set of topcontributing subreddits became less consistent. Each new yearcomes with new meme beachheads.We quantify the degree of change in subreddit ranksby computing Kendall’s ( τ ) coefficient between consecutiveyears. Larger τ values indicate more similarity, smaller τ indi-cates less similarity, and a negative τ represents dissimilarity.Figure 5 illustrates τ for each pair of years where solid barsrepresent statistical significance p < and hollow bars viceversa p > ; there were no p -values between 0.01 and 0.05.Until the 2017/2018 pairing the rank correlation trended down-ward, indicating increased turnover in the topmost innovativesubreddits.The 2017 to 2018 evaluation showed a return to high-rankcorrelation, indicating less change in the top-ranked subred-dits. There are a few potential explanations for this behavior.First, this may be due to a major Reddit policy change: be-ginning in June 2017, Reddit removed the default subreddits,which included many /r/pics, /r/funny, and many of the othermost innovative subreddits, and instead introduced /r/popular,which was a mix of posts from various subreddits as a meansto expose new users to a wider variety of communities . Thischange essentially means that users “subscribe” to a wider va-riety of subreddits by default, providing a greater opportunityfor innovations from niche subreddits to become more easilyaccessed. Another potential explanation for this trend rever-sal is due to the fact that the meme set used for our analysisis biased towards more popular, and therefore older, memes.Memes created during the last years of our analysis windoware less likely to have become popular enough to appear in ourtop-memes dataset. This may result in fewer meme entries inmore recent years. Time (Years) K enda ll’ s τ Figure 5: Kendall’s rank correlation coefficient ( τ ) of subred-dit innovation rankings for pairs of consecutive years. Solidbars represent p < and hollow bars represent p > .Subreddits that consistently use new memes before other com-munities are ranked higher, but rankings change each year.A higher τ means more correlation between year-pairs, whilelower indicates more change in their relative rankings. In gen-eral, subreddit beachhead rankings have become less stable,indicating greater turnover in the top subreddits. Changing Dynamics of the MemeEcosystem
Now that we have established some of the consequences of thecompetition of memes in a social media ecosystem, we turnour attention towards the dynamics of collective attention. Ex-isting recent work suggests that these dynamics are accelerat-ing [18], that is, new concepts are becoming viral faster andstay viral for a shorter duration. Instead of focusing on spe-cific cultural artifacts like memes, the previous work on gen-eral collective behavior focused on hashtags on Twitter, com-ments on Reddit, and n-grams in books, etc. Does this accel-eration hold true for memes? This is the basis for
RQ3 : Howhave the dynamics of collective attention on memes changedover time? Are we cycling through memes faster than we werea few years ago?While we find this to be true in some ways, it is not true5 − t − t peak (Days) R m ( t ) = F m ( t ) / F m ( t p ea k ) (A) − − − Relative Loss p ( x ) (B) − Relative Gain2011 2013 2015 2017 2019
Figure 6: (A) Average relative meme-frequency, time-shiftedso that the maximum frequency occurs on day 0. Shaded areasindicate 95% confidence intervals. The width of the primarypeak has not changed, suggesting that memes have not expe-rienced significant acceleration. (B) Probability distribution ofrelative meme velocities divided into gains (right) and losses(left). Points give true distribution values, lines are fitted log-normal distributions. While small magnitude gains and losseshave shifted slightly, larger velocities do not change. Thesestable velocities again indicate that memes have not acceler-ated.when the growth of the community is accounted for. In otherwords, relative to the number of words produced on Reddit, thenumber of memes is not changing. But what about the dynam-ics of individual memes? How have they changed over time?
Investigating Meme Dynamics
Lorenz-Spreen et al. [18] used a variety of methods to analyzecollective dynamics in the online social sphere. Here, we applytheir methodology to our meme dataset.First, we focus on the peaks of memes on Reddit to assessthe pace of collective attention. For each meme, we compute its frequency across all of Reddit each day, such that F m ( t ) gives the frequency of meme m on day t . We also identifythe peak frequency for each meme F i ( t peak ) and when thispeak occurred. To ensure all memes are on the same scale,the frequencies of each meme are then normalized by thatmeme’s peak to get a relative meme-frequency : R m ( t ) = F m ( t ) /F m ( t peak ) . In Figure 6(A), we illustrate the average rel-ative peak frequency R m ( t ) for all memes in our dataset andgroup by the year of each meme’s peak. Overall, there appearsto be no change in peak dynamics over time. The differencebetween the peak and the baseline frequency ( i.e. , frequencybefore and after the peak) remains relatively stable, nor doesit change a statistically significant amount from year to year.Furthermore, the changes seen do not show a trend over time.This suggests that memes have not exhibited a significant ac-celeration over the past decade.Next, we look closer at the velocities of memes. For eachmeme we compute relative gains [∆ F ( g ) m /F m ]( t ) = ( F m ( t ) − F m ( t − /F m ( t − and relative losses [∆ F ( l ) m /F m ]( t ) =( F m ( t ) − F m ( t +1) /F m ( t +1) , where gains are > and lossesare < . We analyze the distributions of losses and gains of allmemes at all times, grouped by year. Both distributions fit wellto a log-normal distribution. Gains and losses are shown inFigure 6(B). While we observe some shift in gains and losseswith small magnitudes, the larger velocities do not change sig-nificantly or regularly across years.Taken together, both of these analyses indicate that oncethe growth of Reddit is controlled for, the collective dynamicsof Reddit memes have not accelerated. Rather, meme dynam-ics have remained remarkably consistent, even surrounding itspeak. Meme Lifespans are Shrinking
The previous analysis raises another interesting question aboutthe collective dynamics of memes: Are meme lifespans grow-ing or shrinking?To answer this question we define the lifespan of a meme asfollows. For a meme with a peak frequency of F m ( t peak ) , thelifespan begins on the first day u where ˆ F m ( u ) ≥ α ˆ F m ( t peak ) .Recall that ˆ F m ( t ) is the normalized meme-frequency and iscomputed as ˆ F m ( t ) = F m ( t ) /B ( t ) . The lifespan ends onthe last day v where the meme experiences a normalized fre-quency ˆ F m ( v ) ≥ α ˆ F m ( t peak ) , such that all days betweenthe beginning, peak, and the end are continuous and above α ˆ F m ( t peak ) . The threshold value α is very small; here wepresent results for α = 0.005, 0.01 , and . Other valuesproduced similar results.By defining the lifespan this way, each meme’s lifespancaptures the majority of its occurrence, but does not includevery early, late, or anomalous uses. The lifespan is also deter-mined using normalized meme-frequencies to control for Red-dit growth. We compute the lifespan length in number of daysfor each meme. For a threshold of α = 0.005 , these lifespansrange from a high of 4140 days to a low of 1 day. (For com-pleteness, we include the full history of Reddit beginning in2005 when defining lifespans.)6
010 2012 2014 2016 2018 2020 A c t i v e M e m e s (A) · − Time (Years) N o r m a li z ed A c t i v e M e m e s Lifespan Threshold α : 0.005 0.01 0.02 (B) Time (Years) A v e r ageL i f e s pan ( D a ys ) Best fit lines-0.25x + 3274-0.20x + 2918-0.17x + 2538 (C)
Figure 7: Results of lifespan analysis on meme set for α = 0.005, 0.01 , and . Lifespan starts on the first day with afrequency ≥ α ˆ F m ( t peak ) , and ends on the last day with frequency ≥ α ˆ F m ( t peak ) , such that all days in the lifespan have afrequency ≥ α times the maximum normalized meme-frequency. (A) Number of active memes per month, where a meme isactive only during its defined lifespan. Overall, the raw number of active memes has increased. The dip in later years is likelythe result of bias toward older memes in our dataset. (B) Number of active memes per month, normalized by total Redditcontributions. Reddit growth is outpacing the number of active text memes. (C) Average meme lifespan (in days) over time andcorresponding best fit lines. Shaded area indicates 95% confidence interval. Over the course of 10 years, the average lifespanhas decreased ( α = 0.005 : Pearson R = − , p -value < α = 0.01 : Pearson R = − , p -value < α = 0.02 :Pearson R = − , p -value < active onall days contained within its lifespan. On any single day withinour analysis window, there may be many active memes. Fig-ure 7(A) illustrates the number of memes active within eachmonth. As expected, the number of active memes has in-creased over time.To more accurately assess the number of active memes, itis important to control for Reddit’s growth. Figure 7(B) showsthe normalized count of active memes, i.e. , the number of ac-tive memes per month divided by B ( t ) . With this normaliza-tion applied, it is apparent that over time, the relative numberof active memes is decreasing. This decrease in the normal-ized number of active memes occurs despite our finding thatnormalized meme-frequency has remained stable (Figure 3).The most likely explanation for these contrasting findings isthat the lifespan of memes is decreasing.We can test this hypothesis directly by computing how lifes-pans have changed over time. Figure 7(C) plots the averagememe lifespan and 95% confidence interval in days for the ac-tive memes within each month. For example, if there were 40memes active in June 2012 and the mean-average lifespan ofthese 40 memes was 2,400 days, then we would plot 2,400 forJune 2012 (and the confidence interval). The lifespan is heav-ily dependent on the α threshold. So, we repeat these calcula-tions for α = 0.005, 0.01 , and . In all cases, we found thatthe average lifespan decreased over time ( α = 0.005 : Pearson R = − , p -value < α = 0.01 : Pearson R = − , p -value < α = 0.02 : Pearson R = − , p -value < α values tested. Theselong-lasting memes have transcended their origins and evolvedfrom memes into slang, maintaining a consistent presence evenas Reddit grows, and other memes come and go. However, de-spite their seemingly ‘undying’ status, these durable memesmust still compete for attention within the broader ecosystem.In a content-consumption system driven by user attention,memes are forced into competition with one another for scarce7ttention. As collective attention decreases, memes appear torise and fall at an accelerated rate. In a system that favors thenewest, freshest content, no meme is immortal. Conclusions
The three research questions in the present work coalesce intoan emerging theory of meme dynamics in online social bul-letin boards like Reddit. Taking an ecological perspective, wehave shown that although Reddit as a whole continues to grow,the fraction of Reddit devoted to text memes is consistent. Thisreinforces the notion of a meme ecology, which, like the eco-nomic and epidemiological perspectives of information diffu-sion, has consequences that derive from limited user attention.We have also shown that the diversity of memes across com-munities is decreasing slightly, even as the number of commu-nities continues to grow. This represents yet another conse-quence of the ecological perspective: as social media commu-nities continue to Balkanize, i.e. , split into narrow and self-referential communities, the number of shared references tomemes appears to be decreasing.The competition among memes is also evident in the in-creasing turnover of beachhead communities. As memes fightfor user and subreddit attention, cycling in and out of collec-tive attention faster, large and general communities are unableto consistently integrate new memes before other smaller com-munities. Instead, subreddits may rise to the top if they happento introduce the meme-of-the-moment, only to quickly fadeinto obscurity.Finally, we have shown that meme lifespans have decreasedsignificantly. Yet, unlike similar work on general n-grams,hashtags, citations, etc., we do not find that all aspects ofmeme dynamics are accelerating, and even the accelerationsare bounded by the effect of increasing competition for lim-ited user attention. The patterns of relative meme growth, evensurrounding a meme’s peak, remain relatively unchanged bythe expansion of Reddit. And although the absolute number ofmemes active on Reddit has increased over time, this growthhas been outpaced by the growth of Reddit itself.It is important to recognize the limitations of this study.Our evaluation is principally limited by the KnowYourMemedataset. Because the popularity metric is accumulative onKnowYourMeme, it is likely that newer memes, which havenot yet accumulated their full/final popularity, are less likelyto appear in our dataset. Our focus on the textual artifactsof memes may also limit the generalizability of our findings.Much of the online meme culture, especially recently, is con-veyed through visual depictions of memes [31]. We necessar-ily assume that textual representations of visual memes followproportionately, but we are unable to validate this claim in thecurrent work. Future work should endeavor to confirm thesefindings on visual imagery. Finally, the present work used astrict text-matching algorithm to identify memes. Additionalfollow-up work is needed to better understand and trace howthese memes evolve and how the shape of a meme’s popularityand evolution affects its lifespan and reach.
Acknowledgements
We would like to thank Satyaki Sikdar for his help prepar-ing this manuscript. This work is funded by the US ArmyResearch Office (W911NF-17-1-0448) and the US DefenseAdvanced Research Projects Agency (DARPA W911NF-17-C-0094).