A Long-Term Analysis of Polarization on Twitter — TEI-tagged view

Kiran Garimella, Ingmar Weber · 2017 · political-science · arXiv:1703.02769 · full text at the source · TEI xml · tagged edition · index · concepts · authors
Where this record's text came from. faceted 2026-08 by reading the locally held text (pdftext); every evidence string verified as an exact substring of that text before merging. Short ICWSM pre-print (2.6k words), which is why the record is comparatively sparse. Claim type is 'existence' — the paper's contribution is the demonstration that an increase occurred and its magnitude, not a mechanism for it; the authors explicitly decline to adjudicate the causal debate. The 'method' vocabulary supplied does not include a term for large-scale observational social-media data analysis, so 'observational-data-analysis' was coined; the design is longitudinal and correlational, with statistical testing (augmented Dickey-Fuller, t-test on a linear slope) but no experiment or simulation. The paper reports a significance test on the hashtag time series only; no reliability or robustness statistics are given for the follow/retweet measures. 2026-08-14 and 2026-08-15 schema-0.3 passes: every quote verified as an exact substring of the staged text and anchored at merge time; concept terms verified present; every edge endpoint an existing node. Update, 16 September 2026: EXCEPTION TO THE DATED PASS ABOVE, on this record only: this record carries 1 composite quote field - a quote assembled from two or more passages joined by an ellipsis. A COMPOSITE IS NOT AN EXACT CONTIGUOUS SUBSTRING of the staged text and is deliberately not anchored: each of its parts is verified separately at the offsets in evidence composite spans, and a part occurring more than once carries span null rather than a guessed offset. So the 'every quote verified as an exact substring' clause of the dated pass above DOES NOT HOLD for those fields, and never did - the parts were verified, the whole was not. Nothing is deleted, re-grounded or withdrawn: this writes down an exception that was always true of composites and had not been recorded, so a reader was told more than the pass had checked. 2026-09-16 the project CORRECTION TO THE EXEMPTION ABOVE, SAME DAY: THE EXEMPTION DOES NOT APPLY TO THIS RECORD. Its evidence composite spans row(s) are FOSSILS of a 2026-08-25 composite marking that was superseded by a 2026-08-26 re-slice; the quote is an exact contiguous substring of the staged text, so the dated substring claim above holds for it WITHOUT exception. The clause is left in place with this correction beside it rather than removed, so that the error and its repair are both on the record.
1 quote on this page was cut from a different copy of this article. This project holds two extractions of this paper: the plain text every other quote here is anchored in, and the publisher’s own HTML edition, which we are not licensed to republish. It is verbatim in the second and cannot be found in the first — not because the tagging is wrong, but because the extraction damaged the passage: a page number dropped into the middle of a number, a formula moved out of its sentence, a ligature where two letters belong. The record names the copy for each one. The quote is the paper’s; the extraction is not.
Other fields define these differently the same word, defined another way in another discipline
echo chamber 4 fields · social media 4 fields · polarization 2 fields
Tags on this paper every tag the record carries, whether or not the words occur in the text below — a number is how many papers in the corpus carry that tag; a tag with no number is unique to this paper
political polarization2 echo chamber6 social media10 network analysis20 polarization8 leaning2 hashtag polarization observational-study83
Method, as described: observational-data-analysis

Our tag layer for this paper

Cross-disciplinary analysis
content-tags & facets: phenomenon · claim-type · cross-domain-transfer · mechanism · claim-relation · replication-status · limitation — grounded in the full text
phenomenonpolitical polarization on Twitter— “In this paper, we try to answer the question of whether political polarization in the US on Twitter has increased over the last eight years.”
claim-typeexistence— “Our analysis shows that online polarization has indeed increased over the past eight years and that, depending on the measure, the relative change is 10%-20%.”
method — evidence— “We analyze a large longitudinal Twitter dataset of 679,000 users and look at signs of polarization in their (i) network - how people follow political and media accounts, (ii) tweeting behavior - whether they retweet content from both sides, and (iii) content - how partisan the hashtags they use are.”
transferfrom network science / computational social science: social-network-structure analysis applied to measure political polarization on Twitter— “we collect data from Twitter related to both social network structure and tweet content for a large set of users (679,000) engaging with US politics”transfers[0]
mechanismthe time a user began following is ESTIMATED, from the reverse-chronological order the API returns followers in, lower-bounded by each follower's account creation date— “This method is based on the fact that the Twitter API returns followers in the reverse chronological order in which they followed and we can lower bound the follow time using the account creation date of a user. So, as at least some of @BarackObama’s followers started to follow him right after creating their Twitter account, this leads to…mechanisms[0]
mechanismeach user's leaning is a beta-binomial coin-bias estimate - a uniform prior over the two sides, then one increment per follow or retweet the paper's REASON for the Bayesian treatment - that a single act from one side is a weak signal - is the sentence immediately before this one, and widening to reach it pulls in a footnote the extraction has interleaved into the body ('4Since the Twitter API restricts us to the last 3200 tweets'), so the tag is trimmed instead— “Before observing any evidence, we gave each following (retweeting) user a uniform prior probability to follow (retweet) seed users from either side. Concretely, we used a beta distribution with a uniform prior (α = β = 1), where α measures the left leaning and β the right leaning. Then every follow (retweet) to either side increases the count…mechanisms[1]
mechanismpolarization is defined as DISTANCE FROM BALANCE rather than as leaning, so a strongly left and a strongly right user score identicallymechanisms[2]
mechanisma hashtag inherits its leaning from the users who used it that week, and users who did not retweet a seed account that week contribute nothing
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
mechanisms[3]
mechanismtwo explicit noise controls chosen because the early years are thin: a minimum of five users per hashtag, and a five-week moving average
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
mechanisms[4]
mechanismautomated and bad-faith accounts are handled BY THE PASSAGE OF TIME rather than by detection - the study relies on Twitter having suspended them in the years before collection
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
mechanisms[5]
builds-on the hashtag-leaning methodology of [15]
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
claim_relations[0]
builds-on Meeder et al. [10] follow-time estimation method
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
claim_relations[1]
extends Andris et al. [2] (partisanship of the US Congress)
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
claim_relations[2]
extends Liu et al. [9] (seven-year longitudinal Twitter analysis)
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
claim_relations[3]
sensepolarization - STIPULATED AS RESTRICTION, not as hostility or extremity: a tendency to be restricted to one side of the spectrum when obtaining or engaging with political information
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
senses[0]
sensepolarization - AS A NUMBER: twice the absolute deviation of a beta-posterior leaning from 0.5, so it measures distance from a balanced diet on a 0.0 to 1.0 scale and nothing else
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
senses[1]
sensepolarization - AS LEXICAL DIVERGENCE: two sides that describe the same thing in completely different words, the paper's own example being global warming versus climategate
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
senses[2]
sensethe term's scope - FIXED BY STIPULATION IN A FOOTNOTE: every later use of the bare word is declared to mean political polarization
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
senses[3]
controlthree separate questions, each answered from A DIFFERENT TYPE OF INFORMATION, rather than one measure carried through — held — rules out a single data source's idiosyncrasies standing in for the phenomenon - polarisation measured only through, say, retweets is a fact about retweeting until a second and third instrument agree
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[0]
edgepolarization —operationalised-as→ leaning
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concept_edges[0]
audithashtag polarization —is-a→ polarization — Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but endpoint by anaphora: the section is headed 'Hashtag Polarization'; the span writes 'polarization of hashtags'.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concept_edges[1]
outcome (stated by the tagger, no quotation)control — heldcontrols[0]
for which uselimitation — any longitudinal claim: API LIMITATIONS HINDER SUCH STUDIES - only most-recent activity is retrievable
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[0]
for which uselimitation — the authenticity of the measured activity: WE DID NOT EXPLICITLY ATTEMPT TO DETECT ASTROTURFING AND OTHER TYPES OF AUTOMATED TWEETS
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[1]
for which uselimitation — the content measure, with the boundary decision stated: HASHTAG HIJACKING COULD STILL AFFECT OUR ANALYSIS, THOUGH THESE EFFECTS ARE ARGUABLY ALSO PART OF THE POLITICAL LANDSCAPE AND SHOULD BE INCLUDED
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[2]
for which uselimitation — any causal reading: the study cannot settle whether social media causes, reflects or reduces offline polarization
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[3]
for which uselimitation — the election-period pattern: FOR THE 2010 MIDTERM ELECTIONS, HOWEVER, THIS OBSERVATION DOES NOT HOLD, POTENTIALLY DUE TO NOISIER ESTIMATES BASED ON FEWER ACTIVE USERS
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[4]
for which uselimitation — the temporal coverage of the analysis: WE ONLY CONSIDER TWEETS FROM SEPTEMBER 2009 ONWARDS ... SINCE THE VOLUME FOR EARLIER TWEETS IS LOW
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[5]
for which uselimitation — the year-by-year following curve: follow dates are estimated by the method of Meeder et al., whose accuracy is reported to hold for users with millions of followers, while the analysis uses all cases with estimated follow dates from January 2009 onwards
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[6]
for which uselimitation — the hashtag-polarization series: the procedure that produces it - leaning assignment, volume correction and smoothing - is taken from another paper, and this one refers the reader there for details
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[7]
for which uselimitation — a per-user polarization value: it is the mean of a beta posterior that starts from a uniform prior over left and right and is updated by each observed follow or retweet, so a user with few observed actions is scored largely by the prior
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[8]
replicationuntested
limitationTwitter API 'most recent activity only' limitations hinder longitudinal study
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[0]
limitationAutomated tweets and astroturfing were not detected or removed.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[1]
limitationHashtag hijacking could still contaminate the content measure.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[2]
limitationThe study cannot settle whether social media causes, reflects or reduces offline polarization.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[3]
limitationThe election-period pattern in hashtag polarization does not hold for the 2010 midterms, probably because of noisier early estimates.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[4]
limitationPre-September-2009 tweets were excluded because their volume was too low.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[5]
limitationThe follow times underlying the whole time series are estimated rather than observed, and the accuracy attributed to that estimator is reported second-hand and only for accounts with millions of followers.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[6]
limitationThe content measure is not specified in this paper; its method is applied from another work and the reader is sent there for the details.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[7]
limitationEach user's polarization value is a posterior belief that begins from an assumed balance between the two sides, not a summary of that user's observed behaviour alone.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[8]
Content tags
content-observations: finding · quantity · variable · definition · key-term — grounded in the full text
findingOnline political polarization increased over the past eight years, a relative change of 10-20% depending on the measure.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.findings[0]
quantity679,000 users — size of the longitudinal Twitter dataset
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.quantities[0]
quantity10%-20% — relative increase in online polarization over eight years, depending on measure
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.quantities[1]
quantityeight years — span of the longitudinal analysis (two presidential + two mid-term elections)
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.quantities[2]
evidence status notequantity — QUOTE REPAIRED: the extractor split a hyphen-space and the quote was recorded faithfully with the damage in it, which made it unanchorable. The repaired string is an EXACT SUBSTRING of the staged text - that is why it was accepted, not because a rule produced it. The text as originally recorded is kept in evidence as extracted.content_tags.quantities[2]
quantity> 60% — share of Americans who get news from social media (Pew)
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.quantities[3]
definitionecho chamber
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.definitions[0]
key-termspolarization, Twitter, users, political, retweet, hashtags, network, partisan, content
Concepts
terms this paper carries, each with the sentence it was cut from — the layer that joins one paper to another. Terms with no quote yet are on CONCEPTS.html.
conceptecho chamber
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concepts[1]
conceptpolarization
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concepts[4]
conceptleaning
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concepts[5]
concepthashtag polarization
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concepts[6]
conceptpolarization
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concepts[7]
Statistics — cross-field join keys
field-invariant statistical terms, used in their statistical sense (gated on a number / symbol / test). A p-value or a standard deviation means the SAME thing in physics, biology, psychology and sociology — so these are the strongest cross-field join keys. Grounded verbatim.
Bayesian
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.statistics[0]
evidence status noteBayesian — QUOTE REPAIRED: the extractor split a hyphen-space and the quote was recorded faithfully with the damage in it, which made it unanchorable. The repaired string is an EXACT SUBSTRING of the staged text - that is why it was accepted, not because a rule produced it. The text as originally recorded is kept in evidence as extracted. THE QUOTE CONTINUES A SENTENCE THAT THIS COPY CUTS IN TWO, AND ITS FIRST WORDS ARE NOT PART OF THAT SENTENCE - a footnote stands between it and the words it follows, which read 'not necessarily a strong signal', and the quote opens with the end of that footnote's split URL.content_tags.statistics[0]
mean μ as written: mean of
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.statistics[1]
evidence status notemean — QUOTE REPAIRED: the extractor split a hyphen-space and the quote was recorded faithfully with the damage in it, which made it unanchorable. The repaired string is an EXACT SUBSTRING of the staged text - that is why it was accepted, not because a rule produced it. The text as originally recorded is kept in evidence as extracted.content_tags.statistics[1]
p-value p as written: p < 0.0001
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.statistics[2]
t-test t
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.statistics[3]
evidence status notet-test — QUOTE REPAIRED: the extractor split a hyphen-space and the quote was recorded faithfully with the damage in it, which made it unanchorable. The repaired string is an EXACT SUBSTRING of the staged text - that is why it was accepted, not because a rule produced it. The text as originally recorded is kept in evidence as extracted.content_tags.statistics[3]

When we have changed our mind. Some entries in the table begin with a word in capitals and the reason for it. EVIDENCE CORRECTED — the finding still stands, but we had quoted the wrong sentence from the paper, and the quotation has been replaced with the right one. RETRACTED — the entry itself was wrong; it stays on the page, marked, with the reason, rather than being deleted. WITHDRAWN AND REPLACED — the entry was wrong, and a corrected version of it appears in the entries below. Each mark carries its own reason, in brackets, because the reasons differ from one entry to the next. An entry we have WITHDRAWN is removed from this page and kept in the record, with its reason. A line reading Audit and a date is a later re-reading of the entry against its whole sentence: DOUBTFUL means it was kept, and the reason says what is loose about it. Quotation marks inside the tagger's sentence. Where a tag is the tagger's own sentence, a phrase in quotation marks inside it is borrowed from the paper — the tagger's wording around it is not. The paper's own sentence is the evidence quote for that row; on this page it is withheld with the article, and the article is at its publisher. Nothing inside quotation marks anywhere on this page is ours: if it is quoted, it is the paper's. Whose words a concept carries. A concept entry records a term the paper itself uses, so the term, the sense given for it, and its evidence are the paper's own words, quoted where the paper fixes them. This is the opposite of a sense entry in the tag table, which is the tagger's sentence about how the paper uses a term. Where a concept entry could not be grounded in the paper's words, the entry says so on its own row.

Tag layer © the Meta-Tagging Project, CC BY 4.0. The paper text is © its authors/publisher and is linked, not reproduced. Excerpts shown are short quotations for identification and verification. · back to index · concepts · authors · עברית
© 2026 Shir Sivroni · ORCID 0009-0000-2597-2824