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Measuring User Influence in Twitter: The Million Follower Fallacy
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Directed links in social media could represent anything from intimate friendships to common interests, or even a passion for breaking news or celebrity gossip. Such directed links determine the flow of information and hence indicate a user's influence on others — a concept that is crucial in sociology and viral marketing. In this paper, using a large amount of data collected from Twitter, we present an in-depth comparison of three measures of influence: indegree, retweets, and mentions. Based on these measures, we investigate the dynamics of user influence across topics and time. We make several interesting observations. First, popular users who have high indegree are not necessarily influential in terms of spawning retweets or mentions. Second, most influential users can hold significant influence over a variety of topics. Third, influence is not gained spontaneously or accidentally, but through concerted effort such as limiting tweets to a single topic. We believe that these findings provide new insights for viral marketing and suggest that topological measures such as indegree alone reveals very little about the influence of a user.
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“artificially inflating the number of followers can also be finalized to make an account more trustworthy and influential, in order to stand from the crowd and to attract other genuine followers [5].”
From Fame for sale: Efficient detection of fake Twitter followers (2015) · cites this paper as [5]
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“Linking biases impact the study of, e.g., social networks structure and evolution, social influence, and information diffusion phenomena”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Cha et al., 2010
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“Different graph construction methods can lead to different structural graph properties in the various kinds of networks that can be constructed from social data”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Cha et al., 2010
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Sustained online amplification of COVID-19 elites in the United States
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Twitter's Glass Ceiling: The Effect of Perceived Gender on Online Visibility
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“For instance, someone followed by a small number of celebrities and experts may be able to make a larger impact on public discourse than others with more, but less important followers (Cha et al. 2010).”
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BackgroundCompeting Voices: Marketing and Counter-Marketing Alcohol on Twitter
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“An alternative measure of an account’s influence is thus the extent to which the account’s tweets are forwarded (or retweeted) by followers (Bakshy, Hofman, Mason, & Watts, 2011; Cha et al., 2010).”
BackgroundCombining fuzzy logic and eigenvector centrality measure in social network analysis
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“Another example is the data used by Cha et al. [6].”
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“Moreover, earlier research shows that top Twitter users – which often overlap with offline categories such as news organizations, celebrities, or politicians – hold a disproportionate amount of influence on Twitter (e.g. Cha et al., 2010).”
User trustworthiness in online social networks: A systematic review
Alkhamees, M. A., Al-Saleem, S. M., Al‐Qurishi, M., Alrubaian, M., & Hussain, A. (2021) · Applied Soft Computing · doi:10.1016/j.asoc.2021.107159 · Cited by 54
Reachability querying: an independent permutation labeling approach
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Who watches (and shares) what on youtube? and when?
Abisheva, A., Garimella, V. R. K., García, D., & Weber, I. G. (2014) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/2556195.2566588 · Cited by 47
“Apart from demographics, Twitter has also been studied from other perspectives: prediction of trends/hashtags [2, 34, 19]; notions of influence in Twitter [6] and using Twitter predictive data for elections and discovering political alignment of users [8, 9].”
BackgroundLee, K., Mahmud, J., Chen, J., Zhou, M. X., & Nichols, J. W. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1405.3750 · Cited by 47
“widespread use of social media sites, like Twitter and Facebook, and the ever growing number of users, there has been much effort on understanding and modeling information propagation on social media [1, 2, 6, 14, 17, 25, 27, 29, 30]. Most of the work assumes that information is propagated by a small number of influen…”
Background"On the internet, nobody knows you're a dog": a twitter case study of anonymity in social networks
Peddinti, S. T., Ross, K. W., & Cappos, J. (2014) · Proceedings of the second ACM conference on Online social networks · doi:10.1145/2660460.2660467 · Cited by 128
A framework for understanding online group behaviors during a catastrophic event
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Negative expressions are shared more on Twitter for public figures than for ordinary users
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“…especially those interested in the behaviour of “power users”, user that have disproportionate level of influence on online conversations (Cha et al. 2010), on the basis of a number of popularity metrics (likes, retweets, favourites etc.) Practically, sampling at the top is fairly easy…”
BackgroundOpinion leadership in parliamentary Twitter networks: A matter of layers of interaction?
Borge, R., & Valle, M. E. D. (2017) · Journal of Information Technology & Politics · doi:10.1080/19331681.2017.1337602 · Cited by 46
“In addition, as Cha et al. (2010) noted for the whole Twittersphere and Vaccari and Valeriani (2013) for the case of Italian politicians, the number of followers does not indicate influence in the rest of the communication flows since it is not necessarily linked to receiving the highest number of…”
BackgroundBhowmick, A. K., Meneni, K., Danisch, M., Guillaume, J., & Mitra, B. (2020) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3336191.3371800 · Cited by 46
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Detecting Real-World Influence through Twitter
Cossu, J.-V., Dugué, N., & Labatut, V. (2015) · European Network Intelligence Conference (ENIC) · doi:10.1109/enic.2015.20 · Cited by 45
Canter, L. (2013) · Convergence The International Journal of Research into New Media Technologies · doi:10.1177/1354856513493698 · Cited by 45
“, 2010), user influence (Cha et al., 2010) and broader uses of Twitter by the online population (Honeycutt and Herring, 2009; Java et al.”
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“According to prior studies, scholars have adopted various methodologies for tracking the influentials, such as ones based on followers (Kwak et al. 2010), the PageRank measure (Kwak et al. 2010; Weng et al. 2010), and in-degree, retweets, and mentions measures (Cha et al. 2010).”
Fang, J., Chen, L., Wang, X., & George, B. (2018) · Information & Management · doi:10.1016/j.im.2018.04.003 · Cited by 46
E-Map: A Visual Analytics Approach for Exploring Significant Event Evolutions in Social Media
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“We conducted an experiment with a large-scale Twitter-follow link data set that was provided by MPI-SWS [9] .”
MethodDid You Really Just Have a Heart Attack?
Karisani, P., & Agichtein, E. (2018) · International World Wide Web Conference (WWW) · doi:10.1145/3178876.3186055 · Cited by 52
“g methods that relied on extensive feature engineering, or on external feature augmentation to address the sparsity in the feature space, e.g., for company name detection [40], reputation measurement [5], sarcasm detection [3, 18], and for public health [9, 22]. In the health context, the problem is exacerbated by the…”
MethodInfluentialAcquiring Information through Peers
Herskovic, B., & Ramos, J. (2015) · American Economic Review · doi:10.1257/aer.20181798 · Cited by 46
A social endorsing mechanism for target advertisement diffusion
Lin, L.-F., Li, Y.-M., & Wu, W.-H. (2015) · Information & Management · doi:10.1016/j.im.2015.07.004 · Cited by 47
“Studying social influence can help us better understand why certain information are transmitted faster than others and how we could help advertisers and marketers design more effective campaigns [9].”
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Sharma, N. K., Ghosh, S., Benevenuto, F., Ganguly, N., & Gummadi, K. P. (2012) · ACM SIGCOMM Computer Communication Review · doi:10.1145/2377677.2377782 · Cited by 45
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Sentiment analysis of Hollywood movies on Twitter
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“Similarly Cha et al., [7] compare the number of followers, the number of retweets and the number of mentions as measures and conclude that the most followed users do not necessarily score the highest on other measures.”
BackgroundLookup Tables: Fine-Grained Partitioning for Distributed Databases
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MethodStudying social networks at scale
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Detection of influential nodes using social networks analysis based on network metrics
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Influence of information attributes on information dissemination in public health emergencies
Cai, M., Luo, H., Meng, X., Cui, Y., & Wang, W. (2022) · Humanities and Social Sciences Communications · doi:10.1057/s41599-022-01278-2 · Cited by 47
“Conceptually, user influence is defined as the ability to influence the thoughts and behaviors of others (Cha et al., 2010).”
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Sentiment leaning of influential communities in social networks
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Comment articuler analyse des réseaux et des discours sur Twitter
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An Analysis of Verifications in Microblogging Social Networks -- Sina Weibo
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Hemsley, J. (2019) · Policy & Internet · doi:10.1002/poi3.202 · Cited by 43
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“The ranking of the most influential users differed depending on the measures, like the number of followers, PageRank, number of mentions, and retweets count [5, 39].”
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“Moreover, user influence is also a crucial indicator in both sociology and marketing, as discussed in [10].”
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Gionis, A., Junqueira, F., Leroy, V., Serafini, M., & Weber, I. G. (2013) · Proceedings of the VLDB Endowment · doi:10.14778/2536336.2536342 · Cited by 42
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“point out (Cha et al., 2010), a user’s influence may vary over topics and change with time.”
BackgroundInfluentialInformation propagation model based on hybrid social factors of opportunity, trust and motivation
Wan, J., Chen, X., Du, Y., & Jia, M. (2018) · Neurocomputing · doi:10.1016/j.neucom.2018.12.062 · Cited by 42
Characterising and Detecting Sponsored Influencer Posts on Instagram
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“We take inspiration from past work [18], and begin our analysis of influence by looking at follower counts.”
Influence in Social Media: An Investigation of Tweets Spanning the 2011 Egyptian Revolution
Venkatesan, S., Valecha, R., Yaraghi, N., Oh, O., & Rao, H. R. (2021) · MIS Quarterly · doi:10.25300/misq/2021/15297 · Cited by 50
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“We use Twitter and Facebook datasets with 54 million, and 1, 165 users, respectively [23, 41].”
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Finding twitter communities with common interests using following links of celebrities
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“Existing methods involve large scale community detection on the entire social network before determining the interests of individuals within these communities.”
MethodA Temporal-Topic Model for Friend Recommendations in Chinese Microblogging Systems
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“Recently, there has been an increasing interest in the field of information retrieval, such as event detection and tracking [11], [12], identification of influential people [13], [14], sentiment analysis [15]–[18], and personalized recommendations [19], [20].”
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Delayed information cascades in Flickr: Measurement, analysis, and modeling
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“[11] showed that highly influential users are not necessarily the most followed users.”
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Tchokni, S., Séaghdha, D. Ó., & Quercia, D. (2014) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v8i1.14545 · Cited by 41
“find that while number of followers represents a user’s popularity, it does not say much about social influence (Cha et al. 2010).”
BackgroundMethodInfluentialTracking Influential Individuals in Dynamic Networks
Yang, Y., Wang, Z., Pei, J., & Chen, E. (2017) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2017.2734667 · Cited by 41
“Extracting influential nodes in social networks is also an important problem in social network analysis and has been extensively investigated [17], [18], [19], [20].”
BackgroundRoy, A., Huh, J., Pfeuffer, A., & Srivastava, J. (2017) · Journal of Advertising · doi:10.1080/00913367.2017.1297272 · Cited by 41
“Recent big data research measuring influence in a social media context tends to measure it using various metrics, such as number of followers, number of friends, number of retweets, number of mentions, and frequency of online activities (e.g., Cha et al. 2010; Zhang, Zhao, and Xu 2016).”
BackgroundInfluentialSocial media presence of scholarly journals
Zheng, H., Aung, H. H., Erdt, M., Peng, T., Raamkumar, A. S., & Theng, Y. (2018) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24124 · Cited by 41
Li, X., & Feng, J. (2021) · Public Relations Review · doi:10.1016/j.pubrev.2021.102024 · Cited by 43
Wilson, T., & Starbird, K. (2021) · Proc. ACM Hum. Comput. Interact. · doi:10.1145/3476086 · Cited by 50
“We focused on the most (re)tweeted as a proxy for what was considered the most important by users [6,8,57].”
BackgroundAnalysis of Sentiments in Corporate Twitter Communication – A Case Study on an Issue of Toyota
Stieglitz, S., & Krüger, N. (2011) · Journal of the Association for Information Systems · Cited by 41
Active Microbloggers: Identifying Influencers, Leaders and Discussers in Microblogging Networks
Jabeur, L. B., Tamine, L., & Boughanem, M. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-34109-0_12 · Cited by 40
Identifying influential scholars in academic social media platforms
Li, N., & Gillet, D. (2013) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1145/2492517.2492614 · Cited by 43
“Other researchers [12], [13] also investigated the measures of influence in Twitter by tracking the diffusion of posts across topics and time.”
BackgroundOn the impact of social botnets for spam distribution and digital-influence manipulation
Zhang, J., Zhang, R., Zhang, Y., & Yan, G. (2013) · IEEE Conference on Communications and Network Security · doi:10.1109/cns.2013.6682691 · Cited by 44
“A retweet is a re-posting of someone else’s tweet.”
BackgroundMeasuring user activity on an online location-based social network
Scellato, S., & Cecilia Mascolo, C. (2011) · IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) · doi:10.1109/infcomw.2011.5928943 · Cited by 40
“A high fraction of inactive users has been found also in other online social networking services [3], and Gowalla does not seem to deviate from this behavior.”
BackgroundRetweet networks of the European Parliament: evaluation of the community structure
Cherepnalkoski, D., & Mozetič, I. (2016) · Applied Network Science · doi:10.1007/s41109-016-0001-4 · Cited by 42
“Cha et al. 2010 also compare three different measures of influence: the number of followers, the number of retweets, and the number of mentions—also finding that the most followed users do not necessarily score the highest on the other measures.”
BackgroundYang, J., & Kim, Y. M. (2017) · Journal of Information Technology & Politics · doi:10.1080/19331681.2017.1338174 · Cited by 31
“midterm elections seemingly coincided with previous studies (Cha et al., 2010; Vaccari & Nielsen, 2013).”
BackgroundMethodResultInfluentialSocial Media Use for Crisis and Emergency Risk Communications During the Zika Health Crisis
Hagen, L., Neely, S. R., Scharf, R., & Keller, T. E. (2020) · Digital Government Research and Practice · doi:10.1145/3372021 · Cited by 40
“[9] found that retweets and mentions reflect the influence of a user.”
BackgroundInfluentialLiang, H., & Lee, F. L. F. (2021) · Social movement studies · doi:10.1080/14742837.2021.1989294 · Cited by 40
“Past research has suggested that social movements and opinion leadership can be based on personal characteristics, communication activities, and social network positions (Cha et al., 2010; Gonzalez-Bailon et al., 2013; Huffaker, 2010).”
BackgroundCharacterizing the role of bots’ in polarized stance on social media
Aldayel, A., & Magdy, W. (2022) · Social Network Analysis and Mining · doi:10.1007/s13278-022-00858-z · Cited by 40
Talking to the crowd: What do people react to in online discussions?
Jaech, A., Zayats, V., Fang, H., Mari Ostendorf, E., & Hajishirzi, H. (2015) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d15-1239 · Cited by 46
“Previous studies on Twitter show that the reputation of the author substantially increases the chances of the retweet (Suh et al., 2010; Cha et al., 2010), and reputation is also raised as a factor in Slashdot (Lampe and Resnick, 2004).”
BackgroundA Survey of Twitter Rumor Spreading Simulations
Serrano, E., Iglesias, C. Á., & Garijo, M. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24069-5_11 · Cited by 40
“[2] use Twitter data to gain insights into viral marketing and, more specifically, to compare three measures of influence: indegree, retweets, and mentions.”
BackgroundPANAS-t: A Pychometric Scale for Measuring Sentiments on TwitterPreprint
Gonçalves, P., Benevenuto, F., & Cha, M. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1308.1857 · Cited by 40
“The dataset used in this work includes extensive data from a previous measurement study that included a complete snapshot of the Twitter social network and the complete history of tweets posted by all users as of August 2009 [8].”
MethodSelf-citationInvolvement, Contribution and Influence in Github and Stack Overflow
Badashian, A. S., Esteki, A., Gholipour, A., Hindle, A., & Stroulia, E. (2014) · ERA: Education and Research Archive (University of Alberta) · doi:10.7939/r3-wbr5-yd60 · Cited by 40
Insiders Trapped in the Mirror Reveal Themselves in Social Media
Kandias, M., Galbogini, K., Mitrou, L., & Gritzalis, D. A. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-38631-2_17 · Cited by 39
“In [24], Cha et al.”
Personalized emerging topic detection based on a term aging model
Cataldi, M., Di, L., & Schifanella, C. (2013) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/2542182.2542189 · Cited by 39
Real-time recommendation for microblogs
Zhou, X., Wu, S., Chen, C., Chen, G., & Ying, S. (2014) · Information Sciences · doi:10.1016/j.ins.2014.03.121 · Cited by 39
“pi can be computed by user’s popularity or his influence [10,5].”
BackgroundIdentifying and analyzing researchers on twitter
Hadgu, A. T., & Jäschke, R. (2014) · ACM Web Science Conference (WebSci) · doi:10.1145/2615569.2615676 · Cited by 39
Antecedents of Retweeting in a (Political) Marketing Context
Walker, L., Baines, P. R., Dimitriu, R., & Macdonald, E. K. (2017) · Psychology and Marketing · doi:10.1002/mar.20988 · Cited by 45
“Based on a dataset of 1.7 billion tweets, from over 6 million Twitter users, Cha et al. (2010) compared the number of followers, retweets and mentions for each user and found that the most followed users were not necessarily the most influential in terms of generating retweets.”
BackgroundInfluentialZhang, L., Xu, L., & Zhang, W. (2017) · Asian Journal of Communication · doi:10.1080/01292986.2017.1290124 · Cited by 42
“Users who have a considerable number of followers are considered influential (Cha, Haddadi, Benevenuto, & Gummadi, 2010).”
BackgroundZhou, J., Zhou, S., Yu, J. X., Wei, H., Chen, Z., & Tang, X. (2017) · ACM SIGMOD International Conference on Management of Data (SIGMOD) · doi:10.1145/3035918.3035927 · Cited by 39
Framework for Social Media Analytics based on Multi-Criteria Decision Making (MCDM) model
Muruganantham, A., & Gandhi, G. M. (2019) · Multimedia Tools and Applications · doi:10.1007/s11042-019-7470-2 · Cited by 39
“For example, an influence user on Twitter social media is defined by retweets or mentions [7, 12, 30] whereas the number of likes and comments defines the influence users on Facebook.”
BackgroundTales of emotion and stock in China: volatility, causality and prediction
Zhou, Z., Xu, K., & Zhao, J. (2017) · World Wide Web · doi:10.1007/s11280-017-0495-4 · Cited by 39
“Though it is difficult to determine the investment level or type of Weibo users from their online profiles and stock-related tweets, the number of followers in Weibo is indeed a convincing indicator to measure users’ influence to their online community [8, 25, 41].”
Background
Metadata
- Authors
- Cha, M., Haddadi, H., Benevenuto, F., & Gummadi, K.
- Affiliations
- Max Planck Society (DE)
- University of London (GB)
- Venue
- Proceedings of the International AAAI Conference on Web and Social Media
- Published
- 2010-05-16
- Volume
- 4
- Issue
- 1
- Pages
- 10-17
- ISSN
- 2162-3449 (ISSN-L)
- 2334-0770
- OpenAlex
- W1814023381
- Semantic Scholar
- 1ad8410d0ded269af4a0116d8b38842a7549f0ae
- Cited by
- 3,022
- References
- 21
- Citations by year
- 2026: 44 · 2025: 74 · 2024: 61 · 2023: 83 · 2022: 130 · 2021: 212 · 2020: 184 · 2019: 198 · 2018: 257 · 2017: 266 · 2016: 253 · 2015: 287 · 2014: 329 · 2013: 310 · 2012: 193
- FWCI
- 142.70
- Type
- conference paper
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Proceedings of the International AAAI Conference on Web and Social Media (publishedVersion)
- AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) (submittedVersion)
- Max Planck Digital Library (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Social Sciences › Communication › Social Media and Politics
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Keywords
- user influence, Twitter, influence measures, in-degree, retweets, mentions, directed links, viral marketing, information flow, topic dynamics, influential users
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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