Twitter is a valuable resource for research because of its potential to provide insight into public opinion as well as to identify the most influential sources of information. Mixed-methods exploratory analysis was used to evaluate the discourse on Twitter regarding gifted education. The results of the quantitative analysis of the matrix of connections using NodeXL Pro indicate that gifted education Twitter is a cohesive network and that the top influencers are organizations and educational consultants. Sentiment analysis using Linguistics Inquiry and Word Count (LIWC2015, Pennebaker et al., 2015) software indicates that tweets related to gifted education have a mix of positive and negative emotive tone. The qualitative analyses suggest that gifted education professionals and parents engage in Twitter in similar ways to what has been described in past research: to share interesting articles and videos, to discuss current issues, promote one's ideas, and seek opportunities.
AERA ROGCT SIG [@AERA_GiftedSIG]. (2020, January 30). #AERA20 will be here before we know it! Mark your calendar for these sessions and events from the @AERA_GiftedSIG #gifted [Tweet]. Twitter. https://twitter.com/AERA_GiftedSIG/status/1222869068157349890
2.
AlfredssonE. K.BrobergA. G. (2016). Universal parent support groups for parents of adolescents: Which parents participate and why?Scandinavian Journal of Psychology, 57(2), 177–184. https://doi.org/10.1111/sjop.12278
3.
AllenH. G.StantonT. R.Di PietroF.MoseleyG. L. (2013). Social media release increases dissemination of original articles in the clinical pain sciences. PLoS ONE, 8(7), e68914. https://doi.org/10.1371/journal.pone.0068914
4.
AlpZ. Z.ÖğüdücüŞG (2018). Identifying topical influencers on twitter based on user behavior and network topology. Knowledge-Based Systems, 141, 211–221. https://doi.org/10.1016/j.knosys.2017.11.021
5.
AnspachN. M.CarlsonT. B. (2020). What to believe? Social media commentary and belief in misinformation. Political Behavior, 42(3), 697–718. https://doi.org/10.1007/s11109-018-9515-z
BaronA.TownsendR. (2017). Live tweeting by ambulance services: A growing concern. Journal of Paramedic Practice, 9(7), 282–286. https://doi.org/10.12968/jpar.2017.9.7.282
8.
BatrincaB.TreleavenP. C. (2015). Social media analytics: A survey of techniques, tools and platforms. AI & Society, 30, 89–116. htpps://doi.org/10.1007/s00146-014-0549-4
BommaritoS. (2020). ARGUE LESS, TALK MORE: Engaging in productive conversation on social media. Literacy Today (2411–7862), 38(2), 20–22.
11.
BorgattiS. P.EverettM. G.JohnsonJ. C. (2018). Analyzing social networks (2nd ed.). Sage.
12.
BrittV. G.PaulusT. (2016). “Beyond the four walls of my building”: A case study of #Edchat as a community of practice. American Journal of Distance Education, 30(1), 48–59. https://doi.org/10.1080/08923647.2016.1119609
Del VicarioM.BessiA.ZolloF.PetroniF.ScalaA.CaldarelliG.StanleyH. E.QuattrociocchiW. (2016). The spreading of misinformation online. PNAS, 113(3), 554–559. www.pnas.org/cgi/doi/10.1073/pnas.1517441113
19.
DomínguezS.HollsteinB. (2014). Mixed methods social networks research: Design and applications. Cambridge University Press.
DworkinJ.RudiJ. H.HesselH. (2018). The state of family research and social media. Journal of Family Theory & Review, 10(4), 796–813. https://doi.org/10.1111/jftr.12295
22.
EssaidiA.ZaidouniD.BellafkihM. (2020). New method to measure the influence of twitter users. 2020 Fourth International Conference on Intelligent Computing in Data Sciences (ICDS) (pp. 1–5). https://doi.org/10.1109/ICDS50568.2020.9268726.
23.
FieslerC.ProferesN. (2018). “Participant” perceptions of Twitter research ethics. Social Media + Society, 4(1), 205630511876336. https://doi.org/10.1177/2056305118763366
24.
FindlayK.van RensburgO. J. (2018). Using interaction networks to map communities on Twitter. International Journal of Market Research, 60(2), 169–189. https://doi.org/10.1177/1470785317753025
25.
FruchtermanT. M. J.ReingoldE. M. (1991). Graph drawing by force-directed placement. Practice & Experience, 21(11), 1129–1164. https://doi.org/10.1002/spe.4380211102
26.
GHF Learners. [@gfhlearners]. (2020, January 6). What exactly is twice exceptionality? It’s not so much the services that made the difference in their success, but recognizing how [Tweet]. https://twitter.com/ghflearners/status/1214320849613938689
27.
GigliettoF.RossiL.BennatoD. (2012). The Open Laboratory: Limits and possibilities of using Facebook, Twitter, and YouTube as a research data source. Journal of Technology in Human Services, 30(3–4), 145–159. https://doi.org/10.1080/15228835.2012.743797
28.
GoodyearV. A.ParkerM.CaseyA. (2019). Social media and teacher professional learning communities. Physical Education and Sport Pedagogy, 24(5), 421–433. https://doi.org/10.1080/17408989.2019.1617263
29.
GreenhalghS. P.KoehlerM. J. (2017). 28 Days later: Twitter hashtags as “just in time” teacher professional development. TechTrends, 61(3), 273–281. https://doi.org/10.1007/s11528-016-0142-4
30.
gtchat. [@gtchatmod]. (2019, November 14). Hi, all! My tweets for the next hour will be devoted to Global #gtchat (#gifted #talented) Powered by @TXGifted #TAGT [Tweet]. Twitter. https://twitter.com/gtchatmod/status/1195144429088194560
JangS.MckeeverB. W.MckeeverR.KimJ. K. (2019). From social media to mainstream news: The information flow of the vaccine-autism controversy in the US, Canada, and the UK. Health Communication, 34(1), 110–117. https://doi.org/10.1080/10410236.2017.1384433
JürgensP. (2012). Communities of communication: Making sense of the “social” in social media. Journal of Technology in Human Services, 30(3–4), 186–203. https://doi.org/10.1080/15228835.2012.746079
37.
KatzE. (1957). The two-step flow of communication: An up-to-date report on a hypothesis. Political Opinion Quarterly, 21(1), 61–78. https://doi.org/10.1086/266687
38.
KimA.DennisA. R. (2019). Says who? The effects of presentation format and source rating on fake news in social media. MIS Quarterly, 43(3), 1025–1039. https://doi.org/10.25300/misq/2019/15188
39.
KimmonsR.VeletsianosG.WoodwardS. (2017). Institutional uses of Twitter in U.S. higher education. Innovations in Higher Education, 42(2), 97–111. https://doi.org/10.1007/s10755-016-9375-6
40.
KlarS.KrupnikovY.RyanJ. B.SearlesK.ShmargadY. (2020). Using social media to promote academic research: Identifying the benefits of twitter for sharing academic work. PLoS One, 15(4), e0229446. https://doi.org/10.1371/journal.pone.0229446
Külhaş ÇelikİBüyüktiryakiB.CivelekE.KocabaşC. N. (2019). Internet use habits of parents with children suffering from food allergy. Asthma Allergy Immunology, 17(3), 134–139. https://doi.org/10.21911/aai.485
43.
LiJ.GreenhowC. (2015). Scholars and social media: Tweeting in the conference backchannel for professional learning. Educational Media International, 52(1), 1–14. https://doi.org/10.1080/09523987.2015.1005426
44.
LincolnY. S.GubaE. G. (1985). Naturalistic inquiry. Sage.
45.
LiuB. (2012). Sentiment analysis and opinion mining. Morgan & Claypool Publishers.
46.
LuoT.SickelJ.ChengL. (2017). Preservice teachers’ participation and perceptions of Twitter live chats as personal learning networks. TechTrends, 61(3), 226–235. https://doi.org/10.1007/s11528-016-0137-1
47.
LuzónM. J.Albero-PosacS. (2020). ‘Had a lovely week at #conference2018 ‘: An analysis of interaction through conference tweets. RELC Journal, 51(1), 33–51. https://doi.org/10.1177/0033688219896862
MarshallT. C.FerencziN.LefringhausenK.Suzanne HillS.DenJ. (2020). Intellectual, narcissistic, or Machiavellian? How twitter users differ from Facebook-only users, why they use twitter, and what they tweet about. Psychology of Popular Media, 9(1), 14–30. https://doi.org/10.1037/ppm0000209
MilesM. B.HubermanA. M.SaldañaJ. (2014). Qualitative data analysis (3rd ed.). Sage.
53.
Mindshift. [@MindshiftKQED]. (2020, February 3). District leaders want to make sure qualified students who have been overlooked are truly integrated into the district’s gifted program [Tweet]. https://twitter.com/MindShiftKQED/status/1224442971153522694
54.
MoP. K. H.MalikS. H.CoulsonN. S. (2009). Gender differences in computer-mediated communication: A systematic literature review of online health-related support groups. Patient Education and Counseling, 75(1), 16–24. https://doi.org/10.1016/j.pec.2008.08.029
55.
MurphyS. C. (2017). A hands-on guide to conducting psychological research on Twitter. Social Psychological and Personality Science, 8(4), 396–412. https://doi.org/10.1177/1948550617697178
56.
NAGC. [@NAGCGIFTED]. (2019, November 11). “Treating giftedness as an in-born trait that can be identified by test scores has resulted in severe underrepresentation of high-potential children [Tweet]. https://twitter.com/NAGCGIFTED/status/1194062455225368576
NickersonR. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220. https://doi.org/10.1037/1089-2680.2.2.175
59.
Niela-VilénH.AxelinA.SalanteräS.MelenderH.-L. (2014). Internet-based peer support for parents: A systematic integrative review. International Journal of Nursing Studies, 51(11), 1524–1537. https://doi.org/10.1016/j.ijnurstu.2014.06.009
60.
NieuwboerC. C.FukkinkR. G.HermannsJ. M. A. (2013). Online programs as tools to improve parenting: A meta-analytic review. Children and Youth Services Review, 35(11), 1823–1829. https://doi.org/10.1016/j.childyouth.2013.08.008
61.
PeiS.MuchnikL.AndradeJ. S.ZhengZ.MakseH. A. (2014). Searching for superspreaders of information in real-world social media. Scientific Reports, 4, 5547. https//www.https://doi.org/10.1038/srep05547
62.
PennebakerJ.W.BoydR. L.JordanK.BlackburnK. (2015). The development and psychometric properties of LIWC2015. University of Texas at Austin. https//www.https://doi.org/10.15781/T29G6Z
PettigrewS.ArcherC.HarriganP. (2016). A thematic analysis of mothers’ motivations for blogging. Maternal Child Health Journal, 20(5), 1025–1031. https://doi.org/10.1007/s10995-015-1887-7
66.
PrestridgeS. (2019). Categorising teachers’ use of social media for their professional learning: A self-generating professional learning paradigm. Computers & Education, 129, 143–158. https://doi.org/10.1016/j.compedu.2018.11.003
RehmM.NottenA. (2016). Twitter as an informal learning space for teachers!? The role of social capital in Twitter conversations among teachers. Teaching and Teacher Education, 60, 215–223. https://doi.org/10.1016/j.tate.2016.08.015
RiquelmeF.Gonzalez-CantergianiP.MolineroX.SernaM. (2018). Centrality measure in social networks based on linear threshold model. Knowledge-Based Systems, 140, 92–102. https://doi.org/10.1016/j.knosys.2017.10.029
RodriguezC. [@CTRodGT]. (2020, January 9). A2 I think it’s critical that schools communicate what the research actually says about giftedness. There are so many myths [Tweet]. https://twitter.com/CTRodGT/status/1215443598864461824
74.
RossC. R.ManingerR. M.LaPrairieK. N.SullivanS. (2015). The use of twitter in the creation of educational professional learning opportunities. Administrative Issues Journal: Connecting Education, Practice, and Research, 5(1), 55–76. http://dx.https://doi.org/10.5929/2015.5.1.7
75.
ScheufeleD. A.KrauseN. M. (2019). Science audiences, misinformation, and fake news. Proceedings of the National Academy of Sciences, 116(16), 7662–7669. https://doi.org/10.1073/pnas.1805871115
76.
SegotaJ. [@JohnSegota]. (2020, January 27). “When advanced opportunities are extended to students of color and when teachers receive training and resources, these students thrive alongside [Tweet]. https://twitter.com/JohnSegota/status/1221888638264455171
77.
SENG. [@SENG_Gifted]. (2019, November 9). Having high sensitivity makes #gifted individuals especially susceptible to mental health issues, such as depression and anxiety. Sound familiar? [Tweet]. https://twitter.com/SENG_Gifted/status/1193294728118317061
78.
ShepherdD.GoedekeS.LandonJ.MeadsJ. (2020). The types and functions of social supports used by parents caring for a child with autism spectrum disorder. Journal of Autism and Developmental Disorders, 50(4), 1337–1352. https://doi.org/10.1007/s10803-019-04359-5
79.
ShoemakerJ. [@jeff_shoemaker]. (2020, January 8). Taking something away from some is not equity for all. Expand programs, use different methods of identification. Elimination is just [Tweet]. https://twitter.com/jeff_shoemaker/status/1214892524734730240
80.
SmithM.CeniA.Milic-FraylingN.ShneidermanB.Mendes RodriguesE.LeskovecJ.DunneC. (2010). NodeXL: A free and open network overview, discovery and exploration add-in for Excel 2007/2010/2013/2016, from the Social Media Research Foundation. https://www.smrfoundation.org
81.
Smith-RisserH. (2013). Virtual induction: A novice teacher’s use of Twitter to form an informal mentoring network. Teaching and Teacher Education, 35, 25–33. https://doi.org/10.1016/j.tate.2013.05.001
82.
SnelsonC. L. (2016). Qualitative and mixed methods social media research. International Journal of Qualitative Methods, 15(1), 160940691562457. https://doi.org/10.1177/1609406915624574
Staudt WilletK. B. (2019). Revisiting how and why educators use Twitter: Tweet types and purposes in #Edchat. Journal of Research on Technology in Education, 51(3), 273–289. https://doi.org/10.1080/15391523.2019.1611507
85.
StevensonM.HedbergJ. G.O’SullivanK.HoweC. (2015). Development to learning: Semantic shifts in professional autonomy and school leadership. Educational Media International, 52(3), 173–187. http://dx.https://doi.org/10.1080/09523987.2015.1075100
86.
StraussA.CorbinJ. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory. Sage.
87.
SugimotoC. R.WorkS.LarivièreV.HausteinS. (2017). Scholarly use of social media and altmetrics: A review of the literature. Journal of the Association for Information Science and Technology, 68(9), 2037–2062. https://doi-org.proxy.library.vcu.edu/10.1002/asi.23833
88.
SultanM.BrownE. M.ThomasR. H. (2021). Clinicians embracing social media: Potential and pitfalls. Epilepsy & Behavior, 115, 106462. https://doi.org/10.1016/j.yebeh.2019.106462
TifferetS. (2020). Gender differences in social support on social network sites: A meta-analysis. Cyberpsychology, Behavior, and Social Networking, 23(4), 199–209. https://doi.org/10.1089/cyber.2019.0516
92.
TinatiR.HalfordS.CarrL.PopeC. (2014). Big data: Methodological challenges and approaches for sociological analysis. Sociology, 48(4), 663–681. https://doi.org/10.1177/0038038513511561
93.
TrustT.CarpenterJ. P.KrutkacD. G. (2018). Leading by learning: Exploring the professional learning networks of instructional leaders. Educational Media International, 55(2), 137–152. https://doi.org/10.1080/09523987.2018.1484041
94.
TsugawaS.KimuraK. (2018). Identifying influencers from sampled social networks. Physica A: Statistical Mechanics and its Applications, 507, 294–303. https://doi.org/10.1016/j.physa.2018.05.105
95.
TuckerL. (2019). Educational professionals’ decision making for professional growth using a case of twitter adoption. TechTrends, 63(2), 133–148. https://doi.org/10.1007/s11528-018-0346-x
96.
VeletsianosG.KimmonsR. (2016). Scholars in an increasingly open and digital world: How do education professors and students use twitter?Internet and Higher Education, 30, 1–10. .https://doi.org/10.1016/j.iheduc.2016.02.002
97.
VosoughiS.RoyD.AralS. (2018). The spread of true and false news online. Science (New York, N.Y.), 359(6380), 1146–1151. https://doi.org/10.1126/science.aap9559
98.
WangY.McKeeM.TorbicaA.StucklerD. (2019). Systematic literature review on the spread of health-related misinformation on social media. Social Science & Medicine, 240, 112552. https://doi.org/10.1016/j.socscimed.2019.112552
WestermanD.SpenceP. R.Van Der HeideB. (2012). A social network as information: The effect of system generated reports of connectedness on credibility on Twitter. Computers in Human Behavior, 28(1), 199–206. https://doi.org/10.1016/j.chb.2011.09.001
WoodM. J. (2018). Propagating and debunking conspiracy theories on Twitter during the 2015–2016 Zika virus outbreak. Cyberpsychology, Behavior, and Social Networking, 21(8), 485–490. https://doi.org/10.1089/cyber.2017.0669
103.
XingaW.GaobF. (2018). Exploring the relationship between online discourse and commitment in Twitter professional learning communities. Computers & Education, 126, 388–398. https://doi.org/10.1016/j.compedu.2018.08.010
ZhangZ.AhmedW. (2019). A comparison of information sharing behaviours across 379 health conditions on Twitter. International Journal of Public Health, 64(3), 431–440. https://doi.org/10.1007/s00038-018-1192-5
107.
ZolloF.BessiA.Del VicarioM.ScalaA.CaldarelliG.ShekhtmanL.ShlomoH.QuattrociocchiW. (2017). Debunking in a world of tribes. PLoS ONE, 12(7), e0181821. https://doi.org/10.1371/journal.pone.0181821
108.
ZyoudS. H.SweilehW. M.AwangR.Al-JabiS. W. (2018). Global trends in research related to social media in psychology: Mapping and bibliometric analysis. International Journal of Mental Health Systems, 12(1). https://doi.org/10.1186/s13033-018-0182-6
