Handles Apart
Election wit-bits kind of jostle for a real world retreat
The gist
In the last quarter of 2013, tweets were talking about Nepal’s bid to elect the Constituent Assembly. As in real life, a few authors dominated the social conversation: one in every 100 handles created the most buzz, sharing doubts, fears and hopes about the elections. The last 82 sent one tweet or two each in the entire election period. The remaining 17 were active somewhere in between. These tweets were capable of carrying the campaign messages among urban and rural voters. Undertaking a visual exploration of more than 39,000 tweets, archived over two months around the Election Day, that is, 19 November 2013, this article sheds light on who the talking handles were, what they were sharing, when, with whom, and eliciting what in response from their friends and followers. Rather than predict the election outcome, as several studies of tweets have tried to do, this after-event exploration makes sense of the manifest characteristics of Nepal’s election tweets with the help of numbers, words and visuals and suggests the need for further research in this new frontier of human behavior.
Talking tweets seriously
In the last quarter of 2013, tweets were generating a daily dose or two of wit, gossip and gaffe on Nepal’s fresh bid to elect the Constituent Assembly (CA) and install a political government. As the Election Day approached, authors of motley hues posted their take on assorted topics, including politics, on Twitter, a popular micro-blog. They were sharing what they might have thought would be interesting, important, witty, funny or silly about some news, personal update, idea or cause they had in mind for their followers and friends to discover. Eavesdroppers leaned on the micro-blog wall to tap into the short bits of conversation, each within 140 characters, as they erupted, reverberated, sent ripples jostling for attention over the rim of the digital dungeon or simply disappeared without inspiring much ado.
Each tweet identified its author, the text the author sent online, and the time it was posted. Pulled into archives over two months and put together, the tweets featured some people, place, organization, assertion, and description more often than others, suggesting an exploration of the collection might yield patterns with implications for the conduct of election.
These social media texts were capable of traveling fast among millions of real people. In its report for the last quarter of 2013, Twitter boasted about 241 million average monthly active users, showing an increase of 30% year-over-year, and timeline views of 148 billion (Twitter, 2014). In May 2013, a survey of Twitter users (Acharya, 2013) suggested some 7 in 10 handles posting Nepal related tweets were based in Nepal with the remaining three posting from Canada (20%), Europe (16%), India (12%), and Arab countries (12%). Of the seven, four would be in Kathmandu. The remaining three would be in less urban Lalitpur, Bhaktapur, Chitwan and Kaski. Hence, a safe bet was to expect their tweets could travel among many urban and some rural Nepali voters.
Strangely, however, given the typical disconnect of tweets with the touchy-feely world of humans, who were living long hours of #loadshedding, the messages were equally poised to get lost forever.
Nevertheless, the handles and texts, appearing on and vanishing from the Twitter wall over the campaign, campaign blackout, voting and vote counting periods, created an ongoing buzz, available for public search, view, download and close reading. As if peeping for a while through a window into a bunch of tweets had brought a view in sight worthwhile sharing with colleagues, this article explores the manifest characteristics of 12,071 unique authors and their 30,134 unique texts about Nepal, archived over 62 days, from 24 October 2013 till 25 December 2013.
Recent efforts have assessed the predictive power of tweets in the elections of USA, UK, Germany, Australia and India. Yet the findings are far from conclusive or generalizable (Gayo-Avello, 2012). Unlike in the case of snap polls, critics have pointed out flaws in the sampling of tweets as undermining the veracity of election predictions. To survey the tweets, instead of people, to be able to say who will win or lose vote, all studies, by deduction, boil down to suggesting this: we would need a lot of preparation, including skill, resource, tool and time, way before the beginning of the election campaign.
In Nepal, few instances of public research had examined the election time tweets, erupting around the clock thanks to the work of many humans and automatons, making even a modest effort to understand the engagement of social media with electoral politics urgent as well as novel.
What this article is up to doing
So, instead of assessing the predictive ability of tweets, this after-event reading of the social media texts attempts to make sense of which talking handles, in which phase of the second CA election, were trying to reach which followers and friends, with what vibes, fears and hopes, for the real world to take notice. It will transform the texts into numbers and visuals to support an exploratory narrative of the election communication as it unfolds over the key phases of the CA election of 19 November 2013.
The use of visuals — scatter plots, bars, charts, network graphs, etc— will answer the following specific questions about some visible features of the tweets.
Who authored the tweets and re-tweets about Nepal and election in the last quarter of 2013?
What did they talk about mostly?
Other people. Who were the people appearing in the tweets?
Places. Which places did they talk about?
Organizations. Which organizations received the most mentions?
Topics. What topics prominently figured in the tweets?
Descriptions. What action or description did the tweets suggest mostly?
What was the story about the election that these tweets suggested together?
Coming up in a while, the findings
The findings will show, in certain respects, the tweets reflected an aspect of the real world — a few authors, about 1%, dominated the talk, while thousands of others, more than 82%, sent just a tweet or two each and mostly heard themselves alone in the digital echo-chamber. The study found:
More men, women and machines clustered in the tiny Nepal corner of the Twittersphere as the Election Day approached, sending the highest number of tweets on that historic day compared with the number for every other day of the monitoring period
The size of the handles in terms of followers varied widely, but most had several hundred to a few thousand followers
The top hundred authors sent the most tweets, with the next 500 sending fewer than the most, and another 1,600 sending still fewer. Together, these 2,000 (18%) plus authors sent more tweets than some remaining 10,000 (82%) did
Interactive handles were far fewer than the active handles
They were talking about many things including other tweeple, real people, festivals, sports, travel and politics
They shared some fears, yes, but these fears were challenged, overcome, and replaced by expanding hopes over time
Why explore the tweets
Any systematic effort at understanding the use of social media in relation to people, place and organization, topic of interest and description of entities and action in Nepal’s politics would potentially shed light on the nuances of our expanding digital citizenship, participation and political engagement. Specifically, who our tweeting men, women and machines were and what they were sharing in their texts during a crucial democratic exercise of the nation would be interesting to know for its own sake.
A survey of the Nepali public (Media Foundation Nepal, 2012) had found social media networks, like Facebook and Twitter, were growing popular among Nepal’s young and urban people. The number of blogs and micro-blogs by individuals and professionals had gone up drastically. Online journalism, another facet of the new media, had also seen a surge. Most traditional publications or broadcast outlets, the report said, had their online presence. Scores of online news portals, which included those operated from outside the country by members of the expanding Nepali diasporas, enabled readers and users to directly post their comments and feedback, making participation and engagement a reality.
In the first quarter of 2014, a web information company, Alexa, placed facebook.com on top of the websites people visited the most in Nepal. It ranked Twitter 11th, after Google, Youtube, Onlinekhabar, Yahoo, Ekantipur, Blogspot, Wikipedia, and Nagariknews, among others (Alexa, 2014).
Prominent social and political leaders, such as Devendra Raj Pandey, @DRP39; and Nilambar Acharya, @nilacharya; and election candidates Baburam Bhattarai, @brb_laaldhwoj; Ram Sharan Mahat, @ramsmahat; Kamal Thapa, @KTnepal; and Gagan Thapa, @thapagk; among others, for example, were posting tweets during the election time. Former prime minister Bhattarai had made some important announcements and offered clarifications through tweets before he resigned for Chief Justice Khil Raj Regmi, @KhilRajRegmi, to take over. Bhattarai’s handle, @brb_laaldhwoj, was among the top gainers of followers in Nepal for a good while. Journalists and tech enthusiasts were also swelling the Twitter lists by the day.
In the ten years of Facebook and seven years of Twitter, as the Internet penetration rate grew (Nepal Telecom Authority, 2013), these social networks were assuming increasingly central place in the daily life of urban Nepalis and played a role in fermenting the public opinion. It was commonsense knowledge that the social media had supported the fight to end violence against women, with many Nepali users active in the recent campaigns on Facebook and Twitter. They also played a role in mobilizing public opinion in favor of a well-meaning doctor, who went on a series of fast-unto-death protests for reforms in a teaching hospital of Kathmandu (SolidarityForProfGovindaKc, 2013).
Barely two years old in 2008, Twitter had only a few local authors sending tweets on Nepal’s first CA elections. Among the early adopters, Nepalis, if the names of the few handles found in that regard, lama_2b @lama_2b, Deelip Khanal @deelipk, and harikarki @harikarki, etc., suggested nationality, were apparently very few. In 2012, a newspaper editorial (ekantipur, 2012) waxed eloquent about Twitter saying that the platform could put you directly in touch with those that were shaping the news and views—you no longer even had to rely solely on the traditional media. “It gives you breaking news, often straight from the horse’s mouth. And particularly in Nepal, where journalism is so centralized, it’s become a great medium to find out what’s going on far away from the centre, not just from journalists, but anyone who has access.”
Twitter was clearly beginning to drive some portion of news and social conversation. Nepali print and broadcast outlets were increasingly referring to social media in their news and comments. Some online ‘newspapers’, such as Setopati, (Setopati, 2013) routinely sampled what the social, political and government leaders were saying on the new media platforms and published their views on a daily basis.
Monitoring or archiving the tweets of the election time also made sense because the people tended to share a quick hint through the platform about what they had in mind. A little while earlier, as Election Commission Nepal prepared its mainstream media monitoring framework, an important donor organization had posted a tweet in a casual manner saying that the Election Day in Nepal coincided with the Toilet Day. Before it deleted the tweet in the next breath, a prominent lady author commented in this thread, “but Nepal’s election day, Nov 19, is still World Toilet Day”, bringing the human folly to the fore through what critics have also dubbed is a kind of ‘pointless babble’, a coinage generally bandied about in describing much of the social media content.
Several users, however, were seriously making their business or politics better by employing the social media. Reputed organizations, including the UN and World Bank, ran their social media sites, Facebook and Twitter, among others, competing with other organizations and individuals for attention and followers. Almost all daily newspapers, several television channels and FM stations had online presence, with Facebook and Twitter serving their need for news tips or as platforms to share scoops. The ECN was also gearing up to inform the candidates and voters of its electoral education and preparations through the use of several media, including Facebook and Twitter.
“Whether you are on Twitter or not, the messages you will be hearing from politicians will be shaped by it,” said a noted PR man and blogger (BBC, 2012).
Nepalis, the CMR survey suggested, were on Twitter for news and information (85%), to understand public opinion on current news (59%), for gossiping (56%), to express feeling (50%), for networking (46%), for professional works (31%) and to spend leisure time (30%).The survey reported they tweeted anything they found okay to tweet, although their most popular topics comprised social issues (44%), interesting news (42%), politics (37%), profession (26%) and media (23%).
The most popular inspirations behind sending political tweets, another study showed, were to support (26%), to ridicule (15%) and to provide information without any emotional content (13%). A computer scientist and his team at Canada’s National Research Council had started with a million tweets related to America’s 2012 election, analyzed hashtags like #gop, #Obama and #RomneyRyan2012 and, with the help of crowd sourcing, classified a sample of about 2,000 tweets, with multiple readers assigning one of 11 purposes to each message. Mostly, they found, the tweets showed: negativity–criticism, venting, charges of hypocrisy (Mohammad, 2013).
The social media manager of one Independent Voter Network said there were now more tweets sent every two days than had ever been sent prior to 2008. Since its creation, Twitter had impacted the news cycle considerably. Suggesting the reasons why Twitter mattered in elections, the voter network manager said tweets meant: return to retail politics, real time reaction, #trending topics, debates, fact check, voter participation such as by way of re-tweeting, acceleration of the news-cycle, personal engagement, inclusion of voters, and real time journalism (Susskind, 2012).
On top of all, in a country where the penetration of social media among the people was expanding, it was necessary to make some modest beginning in the direction of exploring or gauging the pulse of public opinion about the CA election on social media, starting, perhaps, with Twitter.
Scope of article
During Nepal’s election campaign of 2013, parties, politicians, their supporters and the general public were using Twitter. The main line of interest that delineated the search, collection and analysis of the tweets was to see how the authors were using the platform to talk about the election. Done after the vote counting was over and an elected government of politicians replaced the election government, the analysis picked up the thread in how the early tweets showed fears about election violence and generated doubts about the possibility of successful or peaceful election. As the campaign picked up and vote happened, the fears fizzled out, giving way to surprises, which then, broke out into cheers.
A few tech-savvy enthusiasts, with access to codes, tools and applications, analyzed the campaign tweets and shared their findings, such as the bomb being a dominant topic, via the social media (Simplify360, 2013). These analyses limited their scope to focusing on a few days of the campaign and voting because Twitter imposed time and rate limits in bulk extraction of old tweets freely.
By planning ahead of the peak campaign period, the current effort gradually built the collection of tweets, pulling the first tweet almost a month before election and the last a month after it. Within the constraints of limited time, skill, resource, tool and technique, tweet handle @japokh used online applications in tracking and archiving the election tweets. Similar freeware later eased the exploration of the collection.
The scope of this article, therefore, will be limited to looking at the handles that sent tweets to end up in the archive and some manifest features of the texts they sent, grouping them in example categories, and interpreting, mostly through a visual exploration, what they read like in different stages of the election process.
Findings: The handles
The following section highlights the findings, in plots, diagrams, charts and graphs, around people, place, organization, assertion and description most frequently appearing in the tweets over the election phases. Brief comments accompany the visuals.
The author-handles. A total of 12,071 unique handles participated in sending tweets, replies or re-tweets about Nepal and election between 24 October and 25 December, over 62 days, in the last quarter of 2013.
The density of their appearance over the period of archiving is the highest for the Election Day. Clearly, more authors sent tweets on that historic day and days closer to it, such as the campaign blackout and immediate vote counting.
The trend in daily count of handles sending tweets in the election time showed a sharp increase around the Election Day, people were using the social media megaphone in talking politics more than they did in the days before and after it.
Their participation in the conversation on electoral politics is also evident in that the authors posted more texts on the Election Day compared with any other single day over the period of monitoring. The diagram below shows this.
Tweeting often, the first 2,186 handles (18%) generated 70% of the buzz, while the last 9,885 handles (82%) sent just one or two tweets each for the entire election time. The remaining 17%, the in-between group, comprised a spectrum of handles from quite active to quite passive.
The following bar diagram shows how the talkative top sent their tweets over the election time.
Of the garrulous 18%, the first 100 were responsible for half the buzz, whereas the next 500 rented the air in the echo-chamber generating a volume of conversation volume equal to that from the remaining 1,586 handles did.
A scatter plot for the senders of the most tweets, calculated as a daily average, over the early campaign, campaign, campaign blackout, voting and vote counting periods, marked by the end dates of these phases, looked like the following:
Very interactive tweeples (VITs). Some handles were more interactive than others. Those most prone to sending re-tweets, for example, are shown in the following diagram.
The very interactive tweeples (VITs) were receiving a number of mentions in tweets and re-tweets from others. The following distribution shows the top VITs clustered by color grouping of frequencies for their mentions.
The 12,071 handles generated 24,265 instances of mentions, as identified by @ marker, in the corpus of tweets. Those receiving the most mentions in the body of tweets for the entire period of monitoring are shown in the diagram below.
The following box plot shows what they were tweeting and re-tweeting. The greener the box the higher the number of re-tweets the text in it received, with the greenest receiving 79 re-tweets and the most faded one receiving 10 re-tweets.
The plot is only an example, and, hence, does not exhaust all tweets. For one, the following text, which received at least 114 re-tweets, is not in it: RT … I am leaving for Nepal tonight to observe an Election there. I will take a week’s rest too. I’ll be back …
Some were receiving replies from fellow handles of various hues. Those with the most replies, with the size showing their importance in terms of followers, are in the following plot by time.
Handles made for nepal and election. Some authors had chosen to include text strings, nepal and election, that were part of the search strings to build this archive, in their handle names. They are in the following lists.
Election related handles. ElectionNepal13, NepalElection, ElectaEditore, Election_USA, electionguide, ElectionTweets2, ElectoralReport, NCElection, pasapelectoral, UK_ElectionNews, elecnep13, Election_Watch, electionista, Cleanelection, NeutralityPolls, F_A_Polls, Polliticko, Nepalvotes, Vote4Nepal, THTNepalVotes, votereportindia, votenet, votesafe, 14votes, Voter_In, Vote3rdPosition
Nepal related handles. asdnepal, AyonNepal, ekaamnepali, ElectionNepal13, gcmcNepal, Goal_Nepal, hamronepal8848, JumlaNepal, kishorenepal, KTnepal, LeoWhitmanNepal, live_nepal, Mad_Hav_Nepal, Nepal_Bot, Nepal_Monitor, Nepal_Time, Nepal_travels, nepalanupama, nepaldiary, NepalElection, nepalitimes, nepalkonews, nepalnews_com, nepalnews24, nepalnewsfeed, NepalNoSora, NepalSamachar, Nepalvotes, NewsFromNepal, pearl_nepal, RaviNepal, redditnepal, RepublicaNepal, RSFNepal, ShineDigiNepal, telegraphnepal, thedatanepal, UpsideNepal, Vote4Nepal, 1stNepali, 3AngelsNepal, Aam_Nepali, AayushreeNepal, Acharyanepal, amicsnepal, aria_nepal, Binaj_APNepal, Blue_Army_Nepal, bluesFromNepal, BolaunNepal, carefree_nepali, ChurchinNepal, cidennepal, cijnepal, ComedyNepal, DFIDNepal, drbishnuhnepal, EatPrayNepal, Ecotournepal, elites38_nepal, encountersnepal, EnergyForNepal, EqualMoneyNepal, FoC_Nepal_eV, forestrynepal, G4HNepal, gamesnepal, GMINepal, Hamro_Nepal, HappyNepal, HSTNepal, ImNepalblog, IndigenousNepal, IslamandNepal, KidashaNepal, LAHURNIPNepal, LeSurajNepalais, libirdnepal, Lo_Nepal, made4nepal, MapsNepal, mountain_nepal, MUFC_Nepal, myholidaynepal, mymynewsnepal, Nagnepal, NCARDNepal, NEFNepal, nepal_adira, Nepal_Cricket, Nepal_deep, nepal1st, nepaladvisor, NepalBasketball, NepalCAM, NepalCricket, NepalDRR, nepaleeidiot, NepaleseAtheist, nepaleseprince, nepalforestfire, Nepalgateway, NepalGiftShop, NepalHoops, nepali_football, Nepali_Wizard, nepalialert, nepalibytes, nepalichristian, NepaliEr, nepaliktm, NepaliPirate, NepaliSagar, nepalisanchars, NepaliSense, NepaliSites, nepalkopage, Nepallitfest, NepalMagazine, nepalournepal, NepalPhotoBlog, nepalpictures, NepalSchoolsAid, nepalsites, NepalSurvey, Nepaltalks, nepaltourtrip, nepaltravel, NepalTravelD, nepalvideonews, NickinNepal, NomadicNepali, NowInNepal, NYCAnepal, nynepal, OldNepal, OurNepal, paddlenepal, PBI_Nepal, philipinnepal, PicturesOfNepal, rajunepal, reportersnepal, saminnepal, sardogsnepal, SESFNepal, shadowofnepal, showtimenepal, TheNepal, travelexnepal, TrekNepalApp, troll_nepal, tutornepal, UKinNepal, UN_Nepal, USEmbassyNepal, Viator_Nepal, WaterAidNepal, womenLEADnepal, XinhuaNepal, aaja_nepal, ArjunNepalarjun, banepali, CalgarianNepali, CountryNepal, cricket_Nepal77, cricketingnepal, cricketofnepal1, eventsinnepal, mynepal00, Nepal33, NepaleseAvenue, nepaligreens, nepaliketi22, nepalisthegreat, NepalSport, PunkazNepal, SonOfNepal, SwankyranaNepal, THTNepalVotes, Yeti4mNepal, AmazingnepalNet, AshishNepal1, europenepal, GlamourNepal, IlamNepal, kumudnepal, nepalibabuu, nepalichater, nepalinews, nepalmonitor, nepalnews, nepaltourismb, risingnepalsoon, SFCG_Nepal, shakyanepal, TheNepalTrust, UNDPNepal, visitnepal2011, weeklynepal, WPDNepal, AAANepal, arunsinghnepal, better_nepal, bihaninepal, BimalNepal, eduparknepal, FACTSNepal, Gauravnepali, GorgeousNepal, justnepalii, nepalabeauty, NepalEcco, NepaleeDai, NepaleseCook, nepalfm, nepalgovin11, Nepali6oro, nepaliketo1, nepalikoradio, nepalinepal, nepalivigilente, NepalNetwork, NepalTeam, NepalTibetTours, nepaltraveltips, nepaltroll, picnepal, PuncozNepal, sextoysinnepal, sizzannepal, SStepsNepal, top_nepal_news, topofworldnepal, UmbrellaNepal, WELNepal, yugalnepal, BlogNepal, cricnepal, droplets_nepal, HelloNepal_, hrtbtnepal, ILeadNepal, Nepal_Church, Nepal_khanal, Nepal_Tech, NepaliNews24, NepalIre, nepalitvserial, nepalkotweet, SwissNepali, udlnepal, URD_Nepal
These handles may have affected the results of related codes. However, their uniform control over different phases of election must have minimized the effect.
Funny handles.
@Yami_LalSalam
बेजट!! बेजट!!!! म बाउनकी श्रीमटी भाकोले सायड णेवारहरुले भोत डेनन्!!! #NepalVotes #Nepal_Election #nepalelections 11/20/2013
@PrachandaNepal Maane mero bhaasan ko demand ta @KimKardashian ko sex tape bhanda charko cha ta. Harek mahina leak huncha. #lalsalam Nov 18
@ Lal_Prachanda, _prachanda
Jite #dhoti leJhur khelyo #Nepal leRamro khelera harya vaye ni chitta bujhthyo baru#india… 11/19/2013
PrachandaLife. @KTnepal This will not last! Baburam promised. #Nepal #NepalVotes 11/20/2013
@brb_kaaldhwoj. RT @aakarpost: Great Analysis on Nepal CA Election Results by @akhanal in Tough Talk / @DilBhusanPathak. http://t.co/P4OAm1TDLJ [Must Watch… 11/26/2013
@WarshingtonPost. #Nepal election puts Maoists, and a nation’s disillusion … #GaganThapa #NepaliCongress 11/18/2013
Some people with their new media skills created handles with somebody else’s names or identifier strings and made funny, silly or simply sinister tweets. @Plaid_Regmi was a parody account for election prime minister Regmi as was the @krr_baaldhwoj, which had placed a hair-ful head in a mugshot of Regmi with the name CJ Khil Raj Regmi written next to it.
Real world names in handles. The variety of ways in which a user could choose the name of the handle made it difficult to say for sure if each reflected the author’s real identity in some way. Twitter asks users for email verification to create their usernames. That, however, does not guarantee the user and username have similarities on which to draw conclusions. Moreover, many people have multiple email accounts. When they sign up for the micro-blog, they can choose handles that leave no trace in the name of who they are.
Even those who follow the guidelines may choose a variety of usernames. The official advice on choosing the username is this: there’s no harm in using your actual name of course, provided someone else has not taken it already! “If your desired username has been taken, choose something that reflects you and how you’ll try to use your Twitter account. There’s no harm in being totally professional, but a little bit of character will make you seem more human (TweetLevel, 2013).”
The information in the profile pages would be helpful in some cases, but, in many others, the authors simply avoided showing their real identity. Reading the profiles of some most popular authors, whose election tweets landed in the spreadsheet archive, shows the nature of the problem.
Even these profile details are not always helpful to establish the fleshy identiy of the authors. Only by piecing together the handle name, profile picture, the description for the handle and some tweets could one confirm a known author.
Complicating the matter, the CMR survey, said one in 10 Nepali users maintained multiple accounts. Twitter verification would enhance the confidence about the person being known offline but it was applicable only in the case of a few Nepali handles, such as @AnupKaphle, @prabalgurung and @DeepakAdk of the analysed archive.
Even with knowing all this, one needed other guarantees that these persons were posting the tweets by themselves. Individuals and organizations deployed some device, software or application to send tweets on their behalf. The sources of tweets that came to the archive via the #nepal string indicated that many people were using mobile devices and tweet scheduling applications. Some had clear markers like @japokh’s UPDATE prefix and END suffix or even better, for example, [auto tweet] or satimage, etc. Several handles, it was visible, pulled texts from online tools for containing certain character-strings and auto-pushed these to their Twitter pages, creating a heady soup of text strings produced by humans and automatons of various persuasions. The tweets collector, @japokh, sent 61 election related tweets over the 62 days of archiving. Of these, only a few tweets were posted by the fleshy author of a real world while all the other tweets on his behalf came from an online push message service, with caps on the number of texts, to pull and push as tweets (dlvr.it).
The following network view shows the picture nodes in a grid involving about 100 handles sorted top down, excluding a few from the topmost ones, as they skewed the results for reasons given below the bar diagram, in terms of the number of tweets they posted during the election time.
Those who posted the highest number of tweets were not always those who talked about election or talked evenly over days, weeks or months of the election period. The following diagram shows the top handles by month in color, as an example.
Noticeable in the above chart is a handle with a bar which is more than half red and a little green, showing that it shared election tweets in the platform later in December and dominated it by producing the sheer number of texts with the key search string or hash tag that built the archive for analysis. Many text strings generated by this handle contained topics outside election. Another handle, Nepal_Time, despite being all green for its presence during the campaign period, sent tweets containing the chronology of nothing but time itself: टिंग ! टिंग ! टिंग ! टिंग! टिंग! अहिले नेपालमा बिहानको ५ बजेको छ #TIME #NEPAL #NST.
PowerCutAlert also contributed regularly to expand the archive but its contents were obviously about load-shedding information.
The variety of handles and texts in the tweeple town presented a colorful world of its own. The relative presence of the handles of all hues in the archive, plotted by colored spheres that grew bigger for higher number of postings on the Twitter wall, produced the following visual.
If each follower, or friend, of the handle looked up each tweet it came their way, the potential reach of all the tweets in the archive could have been immense. The plot below, for tweets in the spreadsheet archive, shows the handles, represented by colour of dots showing size of their followers and the size of dots showing their potential reach among followers.
These handles, with their indicative total size of followers, friends and replies, were using several languages as shown in the following plot. English handles dominated in their reach to followers and friends.
en= english, zh-cn=chinese, ar=arabic, ko=korean, el=greek modern, pt=portugese, ru=russian, it=italian, th=thai, en-gb=english great britain, de=german, hi=hindi, fr=french, id=indonesian, es=spanish, nl=dutch, ja=japanese, da=danish, ir= pl=polish, sv=swedish, ca=catalan, fi=finnish, no=norwegian, ro=romanian (Library of congress)
The following scatter plots show handles grouped for their size of followers, such as more than 100,000, or between 10,000 and 99,999, which sent election tweets over the different phases of Nepal’s CA election in different languages.
Those with fewer than 1000 followers, the majority of handles sending the election tweets, were also using English the most often.
Handles back then — Talking CA I. The following are some of the handles which were tweeting about Nepal’s first CA election back in 2008. Most were international media organizations.
EXAMPLE: HANDLE 2008
