Protests and counter-protests seek to draw and direct attention and concern with confronting images and slogans. In recent years, as protests and counter-protests have partially migrated to the digital space, such images and slogans have also gone online. Two main ways in which these images and slogans are translated to the online space is through the use of emoji and hashtags. Despite sustained academic interest in online protests, hashtag activism, and the use of emoji across social media platforms, little is known about the specific functional role that emoji and hashtags play in online social movements. In an effort to fill this gap, the current paper studies both hashtags and emoji in the context of the Twitter discourse around the Black Lives Matter movement.
AbadiM.AgarwalA.BarhamP.BrevdoE.ChenZ.CitroC.CorradoG. S.DavisA.DeanJ.DevinM.GhemawatS.GoodfellowI.HarpA.IrvingG.IsardM.JiaY.JozefowiczR.KaiserL.KudlurM. (2015). TensorFlow: Large-scale machine learning on heterogeneous systems.
2.
AtkinsA. (2019). Black lives matter or all lives matter? Color-blindness and epistemic injustice. Surgical Endoscopy, 33(1), 1–22.
3.
BaiQ.DanQ.MuZ.YangM. (2019). A systematic review of emoji: Current research and future perspectives. Frontiers in Psychology, 10, 2221–2237.
4.
BastianM.HeymannS.JacomyM. (2009). Gephi: An open source software for exploring and manipulating networks. In Third international AAAI conference on weblogs and social media.
5.
BawnK.CohenM.KarolD.MasketS.NoelH.ZallerJ. (2019). A theory of political parties: Groups, policy demands and nominations in american politics. Perspectives on Politics, 10(3), 71–97.
6.
ChaS. (2020). K-pop boyband bts’ fans match group’s 1 million donation to black lives matter.
7.
ChenY.QuanzengY.YuanJ.LuoJ. (2018). Twitter sentiment analysis via bi-sense emoji embedding and attention-based lstm. ACM multimedia conference (pp. 1–9).
8.
CheongM. (2013). Inferring social behavior and interaction on Twitter by combining metadata about users & messages. PhD thesis. Monash University.
9.
ClarkA.DantzlerP.NicklesA. (2018). Black lives matter: (re)framing the next wave of black liberation. Research in Social Movements, Conflicts and Change, 42, 145–172.
10.
CollinsP. H. (2017). On violence, intersectionality and transversal politics. Ethnic and Racial Studies, 40(9), 1460–1473.
11.
CrenshawK.RitchieA.AnspachR.GilmerR.HarrisL. (2015). Say her name: Resisting police brutality against black women. Centre for Victim Research. Technical report.
12.
CsardiG.NepuszT. (2005). The igraph software package for complex network research (p. 1695). Complex Systems: InterJournal.
13.
DadasC. (2017). Hashtag activism: The promise and risk of ”attention. In So- cial writing/social media: Publics, presentations, pedagogies. Fort Collins, Colorado: The WAC Clearinghouse and University Press of Col- orado.
14.
DanesiM. (2017). The semiotics of emoji. Bloomsbury.
15.
DresnerE.HerringS. (2010). Functions of the nonverbal in cmc: Emoti- cons and illocutionary force. Communication Theory, 20(3), 249–268.
16.
FelboB.MisloveA.SøgaardA.RahwanI.LehmannS. (2017). Using millions of emoji occurrences to learn any-domain representations for detect- ing sentiment, emotion and sarcasm. In Proceedings of the 2017 conference on empirical methods in natural language processing.
17.
FreelonD.McIlwainC.ClarkM. (2016). Quantifying the power and consequences of social media protest (pp. 990–1011). New Media & Society.
18.
GallagherR.ReaganA.DanforthC.DoddsP. (2018). Divergent discourse between protests and counter-protests: #blacklivesmatter and #al- llivesmatter. PlosOne, 13(4).
19.
GrossmannM.HopkinsD. (2015). Ideological republicans and group interest democrats: The asymmetry of american party politics. Perspectives on Politics, 13(1), 19–39.
20.
GwaneL.McCullochG. (2019). Emoji as digital gestures. Language@In- ternet, 17(2).
21.
HagenL.FallingM.LisnichenkoO.ElmadanyA.MehtaP.Abdul- MageedM.CostakisJ.KellerT. (2019). Emoji use in twitter white nationalism communicationProceedings of the computer supported Co- operative work and social computing conference.
22.
HallsmarF.PalmJ. (2016). Multi-class sentiment classification on twitter using an emoji training heuristic. Industrial Management & Data Systems, 118, 1804–1820.
23.
HerringS.DainasA. (2018). Receiver interpretations of emoji functions: A gender perspective. In Proceedings of the 1st international workshop on emoji understanding and applications in social media.
24.
JacksonS.BaileyM.FoucaultB. (2020). Social media and social movements. (pp. 785–794). Kidd: MIT Press.
25.
KiddD.McIntoshK. (2016). Social media and social movements. Sociology Compass, 10(9), 785–794.
26.
KimT.WursterK. (2021). emoji.
27.
KüblerJ. (2019). A review of zeynep tufekci - twitter and tear gas: The power and fragility of networked protest. International Journal of Politics, Culture, and Society, 32(3), 357–363.
28.
KwakH.LeeC.ParkH.MoonS. (2010). What is Twitter, a social network or a news media?Proc. WWW.
29.
LebronC. (2017). The making of black Lives matter: A brief history of an idea. Oxford University Press.
30.
LiM.Ch’ngE.ChongA.SeeS. (2018). Multi-class twitter senti- ment classification with emojis. Industrial Management and Data Systems, 118(9), 1804–1820.
MarsiliN. (2020). Retweeting: Its linguistic and epistemic value.
33.
MillerH.Thebault-SpiekerJ.ChangS.JohnsonI.TerveenL.HechtB. (2016). Blissfully happy” or “ready tofight”: Varying interpretations of emoji. In Proceedings of the international AAAI conference on web and social media.
34.
PedregosaF.VaroquauxG.GramfortA.MichelV.ThirionB.GriselO.BlondelM.PrettenhoferP.WeissR.DubourgV.VanderplasJ.Pas- sosA.CournapeauD.BrucherM.PerrotM.DuchesnayE. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Re- search, 12, 2825–2830.
35.
PervinN.PhanT.DattaA.TakedaH.ToriumiF. (2015). Hashtag popularity on twitter: Analyzing co-occurrence of multiple hashtagsInter- national conference on social computing and social media (pp. 169–182).
36.
PrasadA.SanjanaS.BhatS.HarishB. (2017). Sentiment analysis for sarcasm detection on streaming short text data. In 2nd international conference on knowledge engineering and applications (ICKEA) (pp. 1–5).
37.
Ray ChowdhuryJ.CarageaC.CarageaD. (2020). On identifying hash- tags in disaster twitter data. Proc. Conf. AAAI Artif. Intell, 34(01), 498–506.
38.
RipponJ. (2019). The art of protest. Palazzo.
39.
RobertsonA.MagdyW.GoldwaterS. (2018). Self-representation on twitter using emoji skin color modifiers. 680–683.
40.
SieglerB. (2018). Signs of resistance: A visual history of protest in America. Artisan.
41.
StewartL. G.ArifA.NiedA. C.SpiroE. S.StarbirdK. (2017). Drawing the lines of contention: Networked frame contests within #black- livesmatter discourse. Proceedings of CSCW, 1, 1–23.
42.
SullivanE.SondagM.RutterI.MeulemansW.CunninghamS.Speck- mannB.AlfanoM. (2020). Vulnerability in social epistemic networks. International Journal of Philosophical Studies, 28(5).
43.
TarcaK. (2005). Colorblind in control: The risks of resisting difference amid demographic change. Educational Studies, 38(2), 99–120.
44.
TraagV.WaltmanL.van EckN. J. (2019). From louvain to leiden: Guaranteeing well-connected communities. Scientific Reports, 9(1), 5233.
45.
TufekciZ. (2017). Twitter and tear gas: The power and fragility of networked protest. Yale University Press.
46.
WangZ.CuiX.GaoL.QiY.KeL.ZhangS. (2016). A hybrid model of sentimental entity recognition on mobile social media. Journal on Wireless Communications and Networking, 253.
47.
YangG. (2016). Narrative agency in hashtag activism: The case of #black- livesmatter. Media and Communication, 4(4), 13–17.
48.
YoungR. (2016). Make art not war: Political protest posters from the twen- tieth century. NYU Press.
49.
ZeynepT. (2019). A response to johanne kübler’s a review of zeynep tufekci - twitter and tear gas: The power and fragility of networked protest. Interna- tional Journal of Politics, Culture, and Society, 32(3), 65–69.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
