Australian Carbon Tax

Page 1

DIGITAL METHODS

the australian carbon tax



CONTENTS PART 1 - CONTROVERSY

5

INTRODUCTION

6

CONTROVERSY CHOICE

7

AUSTRALIAN CARBON TAX

8

RESEARCH QUESTION

9

PART 2 - PROTOCOL

11

INTRODUCTION

12

STEP 1 corpus determination

13

STEP 2 reading and categorization of articles

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STEP 3 reading and counting of comments

14

STEP 4 semantic extraction and categorization

16

STEP 5 values consideration

19

PART 3 - VISUALIZATION

21

#1 POLARIZATION

22

#2 VARIETY

26

#2.1 VARIETY PEAKS

30

#3 RELEVANCE

32

#4 PROMINENCE

40

CASE-STUDY

43

CONCLUSIONS

50



PART 1

controversy


part 1 - controversy

INTRODUCTION The increase of carbon dioxide in the atmosphere is one of the main causes of climate change. CO2 emissions are extremely harmful for both the environment and the human health: according to statistics of the WHO (World Health Organization) they directly increase cardiorespiratory diseases, and increasing temperature they intensify the proliferation of vector borne and water borne diseases (cholera, diarrhoea, dengue, malaria).

Many economists believe a tax on CO2 is the most efficient market approach to climate change because it has several advantages, particularly comparing it to other climate change oriented measures such as the cap-and–trade scheme: • Predictable carbon prices • Easier to understand • Revenue can be returned via tax cuts and/or used for public goods;

Several countries (such as Finland, Sweden, UK, New Zealand, Quebéc State, British Columbia), during the years adopted the carbon tax as a measure to ease the burden that human-caused pollution contribute to make. This taxation is a scheme of carbon pricing with the aim to reduce greenhouse gas emissions. Since the early stages of the taxation design, it has always been subject to a big controversy, splitting the public opinion into a side of carbon tax-pro and another side of carbon tax-cons.

On the other side, it has some disadvantages: • there is no limit on the amount of carbon that can be emitted • tax revenues may end up being wasted in special interest spending, or priorities that are only peripheral to climate or sustainability (corn-based ethanol, nuclear., etc).

costs passed 3 Extra on to consumers by price increases

reduce pollution TAX 2 Industries paying the carbon tax 1 CARBON ESTABLISHMENT

PRICE RISE

CARBON TAX

COMPENSATION

6

part of the carbon tax revenue is used to compensate households for price rises

4

Small businesses and households have a price incentive to save energy and buy less pollution-intensive goods and services

demand rises for clean efficiency, products 5 Asenergy and investment becomes more attractive and affordable

intensive industries industries shift toward lower 6 Carbon emissions. Growth in cleaner

energy and carbonsequestering technology

7 Emissions fall


part 1 - controversy

CONTROVERSY CHOICE The field of research has been specified using digital tools that contribute to a more conscious view of the hot spot of the controversy. What at first has been pointed out is that the pattern of web research about this topic changed in the past years. The digital tool Google Trends, show how researches using the query “Carbon tax”, remained mostly constant in the span 2007-2010, while increasing dramatically in year 2011 and reaching a peak in the second half of the year. Comparing the queries “Carbon

tax” and the more general “Climate change” it can be seen that, quite surprisingly, the first overtook the second in July 2011. Looking at the bar chart that Google trends provides, it can be also seen a concentration of researches in Australia and specifically in the English language. This analysis has leaded to focus the research on the more specifical Australian area: in fact, it is in this country that a debate got heated during 2011 summer.

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part 1 - controversy

AUSTRALIAN CARBON TAX Australia is a country where climate change has always been a very significant topic, mostly because, even if very less populated, it is proportionally the first CO2 pro capital producer in the world. In November 2011 the majority of the Australian Parliament, headed by the PM Julia Gillard (leader of Australian Labor Party) with the support of the Climate change and energy efficiency minister Greg Combet, approved the law that prices the CO2 emissions. Under this scheme, around 500 entities will be required to buy permits for each tonne of CO2 emitted: This cost will initially be set at $23, and increase gradually until 2015. Personal income tax will be reduced and the tax-free threshold increased. This politic measure generated a huge controversy throughout the country: most of the population consider this tax an excessive burden on the family outcomes, without a being real help for the environment. Among the main opposers of the tax, the large group of climate change deniers, that criticize the concept of global warming for itself and subsequently consider iniquous and irrelevant this kind of taxation. Other people consider the carbon tax as a possible contribution, even if not resolutive, to a global economy lead towards a better and cleaner planet . The debate soon turned out to be substantially political, because one of the point that Miss Gillard’s government programme focused on, was indeed not to establish the carbon tax. This change in the game in the matter of climate policies, subsequent to the alliance of the labors with the greens, has caused a huge discontent among the population that voted for her. The opposition, headed by Australian Liberal Party’s leader Mr. Tony Abbott, sided sharply against the carbon tax, preferring on the other side the emission trading scheme adopted also in Europe. 8


part 1 - controversy

RESEARCH QUESTION This research focuses on what web users thinks about carbon tax, specifically considering their response to public information sources. In the “sharing era� what counts the most is not only what people say, but particularly how they say it: the preliminary consideration is that if an idea many times is expressed (in a sort of binary code) just in a form of positive/negative, more often it is developed in slight and ambiguous ways. It is remarkable to consider, in addition to a mere statistic work based on the count of different opinions, how an idea can be expressed and supported in its different shades. The attempt is to experiment a sentimental analysis based of a combined work of both human judgment and scientific digital tools. The project questions can be summarized as follows [img 3]

1) What do web users think about Australian carbon tax?

2) How do they express their opinions?

3)Which are the main topics that people presents in support of their ideas?

9


11 links 55

POLITICAL DEBATE

51

32

197

155


PART 2

protocol


time range: last 3 months corpus size: 200 link query: “carbon tax” Australia

GOOGLE\NEWS

part 2- protocol

INTRODUCTION

DMI HARVESTER

MANUAL CLEANING

In the determination of a functional protocol, the first question to ask is which is the most suitable place to find materials. According to the aim of studying users’ point of view, at first they have been considered several different platforms, such as social networks, blogs and video-sharing websites, but they didn’t seem to respond to the basic requirements they had previously been established: clear argumentation and heterogeneity of opinions, pertinence to the input-topic and lack of vulgar language. Subsequently it has been chosen the way of expressing an opinion that most matched these criteria: the comments on articles found on online newspapers, both Australians and non Australians. The major factor that lead the research to focus on these particular field is that commenting an article most of the time implies a stronger interest in the topic discussed in the article itself.

removing links without comments

CORPUS DEFINITION

46 links

READING

CATEGORIZATION

1

2

political debate

3

political acts

4

non-political opinions

popoular reactions

SI

NO

N.R.

*.txt

*.txt

x

5

extra-AU chronicles

*.html *.html

ALCHEMY API *.csv

*.csv

x 5 volte

MANUAL CLEANING manual process digital process

DIVISION BY TOPICS

tools manual steps 12

1

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COUNT

RELEVANCE

WEIGHT

semantic variety polarization

relavance polarization

prominence by topic polarization

12


part 2- protocol

STEP 1_Corpus 1 2

The first step has been a research on news.google.com, with the query “Carbon tax” Australia. Results have been filtered considering a corpus of 200 links, in a time range of the last four months. With DMI Harvester, detection of these 200 links, checking the boxe “Exclude URLs from Google and Youtube”. This corpus made of 200 links, has been manually checked and cleaned following these criteria: 1) Exclusion of “Not found” links 2) Exclusion of links that diverted from the main topic 3) Exclusion of the news websites that didn’t allow comments The corpus has this way been reduced to a total of 46 links.

National abc.net.au news.com.au sbs.com.au

Perth perthnow.com.au

fw.farmonline.com.au

Goonellabah northernstar.com.au Adelaide

adelaidenow.com.au

Goulburn

Brisbane thechronicle.com.au Newcastle theherald.com.au

theaustralian.com.au Sidney dailytelegraph.com.au smh.com.au Canberra canberratimes.com.au

goulburnpost.com.au

Melbourne heraldsun.com.au

Dislocation of newspaper site in Australia 13


part 2- protocol

STEP 2_ reading and categorization of articles Each article has been read and inserted in a specific category. It has been possible to detect five categories according to the article typology: political debate, non political opinions, political acts, popular reactions and extra-australian chronicles. This subdivision is useful in order to achieve a more complete knowledge of the controversy dynamics: in fact depending on the input, the answer may vary considerably.

part 2- protocol

STEP 3_ reading, counting of comments Each comment has been read and divided according to its expression of a favourable opinion about carbon tax or a negative one. It has been introduced a third group of comments that for their particular characteristics couldn’t fit in the mere judgement of pro/cons: the comments that have been considered not relevant because they didn’t express a clear and categorizable opinion, because they diverted from the main topic (in this case, particularly politic dissertations that didn’t include carbon tax itself) or simply because they were a noise source. The result of this preliminary analysis is a spreadsheet that shows the distribution of the consent among the analysed categories. What at first can be seen, on a basis of about 1200 comments, is a sharp predominance of the cons above the pro.

14


15

55

51

32

197

NON-POLITICAL OPINIONS

155

239

5 links

POLITICAL ACTS

5 links

11 links

4 links

11 links 56

POLITICAL DEBATE

POPULAR REACTIONS

176

21

21 3

EXTRA-AU CHRONICLES

42

71

17

NOT RELEVANT 174

PRO 209 CONS 788

SEMANTIC EXTRACTION WITH ALCHEMY API

527

471 words

words

310 words

344 words 15


part 2- protocol

STEP 4_ semantic extraction and categorization At this point, each category was divided in the three sub-categories of pro, cons and not relevant: the last one has however been removed because it wasn’t made of significant data on which to build a semantic analysis. Afterwards, for each category they have been generated two html files containing respectively all the comments in favour and against the carbon tax. Using Alchemy API, it has been obtained a semantic analysis made by 10 csv files that considered concept, entities and keywords. The following step required an interpretation of the raw data the tool had given, and what at first seemed necessary was to consider all the data got from the extraction, not limiting it only to concept or entities. After a brief cleaning of the words detected by the tool but completely not relevant, such as sequences of random letters and numbers or lonely prepositions. They have also been removed the words “Australia” and “Carbon

16

tax”, that were contained in each csv because they were part of the original query. The process developed then into a further categorization ignoring the one proposed by the tool (that automatically detect some fields such, for example, City, People or Organizations). They were generated 12 categories that emerged in a physiological way from the reading of the extracted words, and once merged them in a color subdivision they have been checked and cleaned a second time, taking care of removing the equal words. In addition to these categories it has been added another one that included all the words that, even if pertinent to the carbon tax controversy, weren’t clearly attributable to one of the twelve previously determined. The purpose of this additional category is to show how in a pattern of similar topics what can make the difference is indeed the word that “doesn’t fit in”.


taxes Carbon tax and other taxation in Australia or not

majority party Prime Minister Giulia Gillard, Labour Party and all the majority line-up

opposition party Opposition leader Tony Abbott, Liberal Party all the minority line-up

geographical references Cities and Countries in Australia and all over the world

regulation Protocols (like Kyoto), tradings, carbon prices regulations

climate references All about climate change, global warming and the scientific references

fossil fuels Carbon fossil fuels, like coal, fuel and natural gas

pollutant Emissions of pollutant gases, like Co2 emission

energies Alternative or clean energies

money Micro economics issues, family income, bills, wage

business Macro economics issues, enterprises, multinationals company

istitutions State institutions or non governative organizations

17


Raw .csv data, uncleaned

Cleaned and categorized data

18


part 2- protocol

STEP 5_ value consideration Typically, an Alchemy analysis provides three different measures that can be used to visualize a controversy: count, (only for “entities”) relevance and the total count of the words shown in the csv, that give an idea of the semantic variety in the analysed category. For this research they have been used relevance and words count, used alone or weighted. The weighting is a particularly important factor because one of the main purposes of the analysis is to compare words and topics amongst the same category but also between different categories: in order to do it, it is necessary to convert all the values considered in a comparable base, in this case 100. This way the absolute value become relative and the comparison is possibile. The weighting process starts from the idea that, if both count and relevance can express a lot if considered individually, they have a greater visualizing potential if joined to express a more reliable value.

relevance 2° value

always use the average of relevance of topics relevance

count 1° value

use the percentage to compare counts between different topics count : tot count = x : 100

count * 100 tot count

weight 3° value

(

)

percentage * average 100

try to weighting percentage and average in order to estimate topics prominence 19


0,2756675

0,31832367

0,42790175

0,348631

0,4922675


PART 3

visualization


part 3- visualization

#1 POLARIZATION In the attempt to perceive the predominant topics in the proside and in the cons-side, it has been visualized the polarization graph: in these three graphs it is expressed the polarization of the twelve topics (plus the discriminant category) between the two poles of pro and cons. The closeness of a topic to one of the two vertical axes, reflects the real closeness to the correspondent side. They have been proposed three versions (prominence, relevance, word count) to allow a comparison and an observation of the main patterns.

22


1

Count: this value express how many words belong to each topic. The highest value of each topic is used to set the position on the Y axe.

count 110

110

95

95

discriminate

70

70

geographic references

taxes

50

majority party 30

0

PRO

40

regulation opposition party money pollutants fossil fuels

clean energy business

institutions

climate references

30

0

CONS 23


2

Relevance: this value consider the relevance of each word extract with Alchemy. The highest value of each topic is used to set the position on the Y axe.

relevance 1

1

0,95

0,95

0,70

0,70

pollutants climate references 0,50

0,30

regulation fossil fuels

clean energy 0,50

taxes money business opposition party majority party discriminate

0,30

geographic references

0

PRO 24

0

CONS


3

Prominence: the value used in this graph considers the weighting of both relevance and count. The highest value of each topic is used to set the position on the Y axe .

prominence 110

110

discriminate 95

95

70

70

50

50

30

0

PRO

30

0

CONS 25


REACTIONS POPULAR

26

PRO

64 words

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6

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13

The two graphs show the whole semantic corpus extracted with Alchemy after the operation of checking and cleaning, and it is clearly visible the subdivision in 12 different categories. The aim of these visualizations is to point out the semantic variability for each category. Linking the words that are equal in different categories clearly shows how, for different topics, users can express their ideas in a less heterogeneous way. It can be seen a so called “reticulate of variability”: more links correspond to a smaller vocabulary used to express the same concept. This is particularly significant in order to have a clear and complete view on users’ habits and to understand which are the topics that are closer to the person who’s speaking. As a matter of fact, topics more “official” such as politics or climate change related have a smaller semantic variations, whilst hotter topics such as money and household do actually have a more prominent semantic variability

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#2 SEMANTIC VARIETY part 3- visualization


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POLI TICA LA 51 w ords CTS 4

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66 words

NON POLITICAL OPINIO NS

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NON P O L I T I C AL O P I N I ONS 64 wo rds

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CONS 5

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70 words

POPULAR REACTIONS


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POPULAR REACTIONS 70 words

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4

4

15

2

14

4

10

7

7

on s iat ter var l vo vity es foo ra lgi or g g du po yclin on in ese c arb hin c C the SA pe U uro ing nd E yom isla W urtis uver C co van dia In sia A UK o Ohi dney n lia Si chiga ustra Mi gin A Vir tas rgy s Qan in Ene r plant Orig nuclea MW group rs BG el make s ste try actor ustry indusopean ind nuclear re ower eur mercial nuclear p com mercial com r taxes higheon tax bill carb tax green e tax incom tax es tonne usehold expens extra ho t fuel cosousehold extra h ehold cost extra hous coal fossil fuels ants ef cient coal pl natural gas global warming climate change net ice melt a liar and turncoat Julia Gillard Robert Reich nuclear power nuclear plants civialian nuclear power carbon dioxide greenhouse gas co2 emissions IPCC Canadian enough government Obama courage treasu rainbo ry senat w government ppoli e blac cies gove k holes mass rnment sy sho ive debts srem stup w l eg i d foo islation ma ls ba ternity hy d polic leave Ch pocrite ies Me ina s Ca lbour Ja nada ne Go pan In ulbu A dia rne N sia C orthe C harlt rn E B alifo on nglan d A razil rnia c ustr th oali alia in e c tion n la w ep urr gre bor t or t go ent at pa e s pat ax ob t gov vernm prim st str rty he ses ern en e m eng tic se me t ini ht ste h g d o r ver gove nt nm rnm e n en t t

5

6

2

10

LES ONIC R H AU C RA- 62 words 9 EXT

1

8

ing rm ge wa han bal e c glo limat ane c eth tion rs m axa aye t ax t p s xide tax x cut n dio x ta arbo e ta c com stem in sy ars tax x doll tax ta upid x st w ta ne rate tax s tax intless earner po come me in inco low e me wag gle income sin h inco me rners hig er inco ome ea low er inc rs high ket earne poc er income e family low le incom sing ways bills r polluting ment Thei al govern rnal feder Street Jou Wall naut Ross GarC The GF ry treasu isease chronic d my wife distribution wealth re extremist Julia Gillard ent Gillard governm AL P Juliar Labor government Paul Keating Gillard party greens government Sidney Melbourne Europe India Brazil Greece Darwin Hong Ko top ten ng three ecpolluters Qantas o-crimilals bu s i n big bu ess big po siness Tony lluters libera Abbott Malc ls Pete olm Turn M r Costello bull r . N em o Kyo ission tr ETS to protocading ol car IPC bon cr me C rep edit IPC dicar ort CS C e ca IRO ca rbon gl rbon dioxid cl obal emis e Ro imat warm sion N ber e cha ing M avy t Reich nge M att R A iste idle S l Go r Re y E teve re vkin t lite n Lev itt e rain p xtra ed wo ext rime rke ra mi rs w n ra m ister ing en erg y 11

s ord

3

1

E AT EB D L 4

2

4

16

POL IT IC AL ACT 69 wor S ds 9

29


part 3- visualization

#3 SEMANTIC PEAKS This visualization is an integration of the previous one, in fact it provides a direct comparison between the two poles pro and cons, showing how the same topic can have a more considerable semantic variability in a pole more than in the other. It can also be easily seen a direct comparison between different topic in the same pole.

PRO

CONS

30


31


part 3- visualization

#4 RELEVANCE The second visualization points out categories inside pro and inside cons, in order to allow, varying the research question, the choice of the most suitable variables..

1

These graphs show, for each category, the fluctuation of relevance average of the topics, directly comparing pro and cons. The goal is to understand in which side the words extracted in the semantic analysis are more or less relevant.

0,2756675

0,31832367

0,48723133

0,42790175

0,348631

0,4922675 0,16664514

0,31139223

0,412604 0,26107815

0,60726233

0,688954

0,6130989 0,47307872 0,26706433

0,248339

0,248482

0,35867636

0,46255282

0,37627517

0,54954363 0

32

0,7656872

political debate


0

0,20339638

0,1947815

0,1773812

0,40439

0,36897017

0,700269

0,607876

0,525474

0,51259958

0,6171834

0,5397898

0,4541498

0,33848783

0,3709126

0,406082

0,575914

0,47842825

0,42151733

0,34689465

0,324357

0,335079

0,35172771

0,3556295

0,2904652

popular reactions

33

1


34 0

0,228636

0,5110175

0,3679915

0,324357 0,47582358

0,46621325

0,35444833

0,50519733

0,38833072

0,42183871

0,38440317

0,417701

0,39496575

0,29526854

0,22351122

0,25421021

0,43646356

0,3780886

0,308001

0,262268

extra-Au chronicles political acts

1


0

0,31012

0,41368663

0,327777 0,633552

0,5540624

0,58308775

0,602129

0,601539

0,48898613 0,40143775

0,29374333

0,299182

0,4255355

0,31723343

0,3344389

0,61993467

0,551673

0,476366

0,452245 0,33638767

0,30469

0,320386

0,2793702

0,199354

0,1652945

0,29821938

0,33772264

0,39077425

0,3334165

0,5644705

0,537889

0,33848783

0,33812038

0,311955

0,238675

0,3705923

non-political opinions

35

1

0,987159


0

36

political debate

non-political opinion

extra-Au chronicles

political acts

popular reaction

0,26107815

0,47582358

0,42151733

0,31723343

0,25421021

0,34689465

0,26706433

0,33638767

0,3780886

0,335079 0,46621325

0,35444833

0,35172771

0,30469

0,248482

0,50519733 0,43646356

0,3556295

0,35867636

0,320386

0,308001

0,47842825

0,37627517

0,29821938

0,262268

0,3679915

0,700269

relevance PRO 1

0,987159


37

0,406082

0,412604

0,4541498

0,41368663

0,42183871

0,31832367

0,327777

0,38440317

0,39077425

0,40439

0,42790175

0,6171834

0,61993467

0,551673

0,48898613

0,417701

0,348631

0,29374333

0,33848783

0,33848783

0,537889

0,4922675

0,4255355

0,39496575

0,3709126

0,2756675

0,16664514

0,299182

0,22351122

0,311955

0,31012

0,5110175

0,5644705


0

38

political debate

non-political opinion

extra-Au chronicles

political acts

popular reaction

0,575914

0,47307872

0,589291

0,601539

0,48795433

0,37625007 0,3344389

0,54954363

0,46255282

0,452245

0,324357 0,324357

0,248339

0,199354

0,1947815

0,323406

0,29526854

0,228636

0,1652945

0,1773812

0,33772264

0,473122

0,38833072

0,2904652

relevance CONS 1


39

0,35918658

0,448352

0,476366

0,633552

0,5397898

0,48723133

0,40143775

0,36652567

0,3334165

0,36897017

0,60726233

0,5540624

0,50598233

0,525474

0,7656872

0,688954

0,58308775

0,52075925

0,607876

0,6130989

0,602129

0,51259958

0,427515

0,33812038

0,31139223

0,2793702

0,238675

0,20339638

0,4385238

0,3705923


CONS

part 3- visualization

#5 PROMINENCE The importance of this graph is its being summarizing and double-readable. In fact, it allows a multiple comparison between the two poles pro and cons, topics and categories. If in the central bar it can be found the overall flows of topic, the polarity on the sides allows to understand how these flows are divided and, at the same time, to also have a singular vision inside the topics of one specific category, made more easily understandable with bar charts. This way, it can be considered a summary and a deepening of the previous visualizations. Is goal is to express the value of “prominence� of the topics inside categories, weightening word count and relevance.

69,8 62,6

political debate

38,8 47,3 26,2 46,8 12,3 23,1 3,1

32,9 10,9 38,6 12,7 17,4 37,4 6,3 31,7 14,2 5,6

popular reaction

popular reaction

90,5 33,2 30,8 23,2 17,4 12,7 31,6 80,6 15 8,3 52,3

non-political opinions

131,7 47,5 49,5 34,9 36,4 5,2 25,1 17,3 9,4 21,2 6,2 52,3

political act

48,3 84,4 13,8 24,2 34,2 19,3 34,3 3,3 75,2

extra-au chronicles

40,6 43,2 13,6 16,4 16,1 76,4 15,7 5,7 14 8,1 13,1 55,6

political debate

95,8

35,4 22,9 7,2 75,3 25,2 53,2 27,6 24,5 31,5 28,5 5,2 85


9,4 27,1 37,6 36,3 58 29,1 5 13,4 37 15 15,3 13,8 62,5

political debate popular reaction

32,9 10,9 38,6 12,7 17,4 37,4 6,3 31,7 14,2 5,6 5,2 38,5 140,9

non-political opinions

40,6 43,2 13,6 16,4 16,1 76,4 15,7 5,7 14 8,1 13,1 55,6

22,1 7,2 43,3

30,6 8,6 36,5

political act

6,1 21,1

29,7 36,6 20,8

30,1 15,4 43,4 19,7 34,8 9,1 28,3 12,3 83,4 27,8 52,3

PRO

extra-au chronicles

223,9

41


OC

SN


PART 4

case study


1

pension increase climate chang Global warmin capita carbon emissio Carbon dioxid e ti addi on fossilalfug Natur clean ener gas turb ur Energy siso la g le g in d a IR p carbon tr

2

2

CASE-STUDY

bine bu gas tur protit m supe

3

3

2

political debate’s topic

3

A

6

In order to reach the research goals, it will now be analysed a case-study with the attempt to verify if they are exhaustive and functionals. It has been chosen to consider only one category, specifically “Political debate” and analyse how it can be used as a basis to answer to the research questions.

1. What do users think about carbon tax? As the first graph shows, the analysed comments sharply express the opposition of users to carbon tax (197 vs 56), being them more than double of the users that on the other hand, are in favour to it. Corpus remains even bigger subsequently to the semantic analysis in which, after a manual cleaning of pointless words, they have been analysed 79 for cons and 61 for pros.

56

44

15

55

51

32

197

155

6

POLITICAL DEBATE

TE A B DE L ICA words T I OL 61

11 links

wa


2. How and in which form (language) do users express their opinion? The categories (political debate_pro and political debate_cons) extracted from count graphs show the semantic variety inside categories. Summarized with cirles of different sizes according to the number of connection the word has, it is clear to point out how among the cons there is a less semantic variety: in fact, the words used are the same used in other categories. It can also be notices that in the cons group, even if it has a bigger number of words, there is a smaller number of topics: it results in a reduced semantic variation and a reduced topics amount.

pro

ele cti on c rig amp h t w aign Ton ing Ab yA Art bbo righ nutt bott hur tt c t w ers Sin ome ing Lib mino od d e T pur ral p rity g ony Re inos y e be arty ove Ab ith leag of A rnm bott uer ust ent ed ral sce voting ia d fre pti desp irect ae tradecs desp pu erate mction erat re fi an e me ctio asur n es weal p th re ma olicy distr rines ibu Youtution Canadia Boga b e enough cnogovernment n Obam Obama urage a treasury rainb senateow government polic black ieh s gove oles massirnment sys sho ve debts rem stupiw leg d foolsislation ma bad ternity l hy polic eave Chinpocrites ies Me a Can lbourn Ja ada e Gou pan In lbu Asi dia rne N a Chaorther C rlt n E Bra aliforn on nglan d A zi ia coa ustra l l t li ia in he c tion n la wo ept g urren grea bor p tax rst ove t p tes arty ob gov rnm rime t str ses ern e m eng sed me nt inis hth t er gov nt ern me nt

16

11

PO LIT I

w

11

79

TE EBA LD CA ords

13

nt me n r ve go nt te ic illard rnme h al at lia G gove ray on tax x t u e r J bo r x b arb n ta la ulia in ta s c rbo tax J arb lou d ca bon nse c dicu nte car nse ri nwa tful x no u ecei n ta ud d rbo x fra ca 2 ta co x ax tax s ta ining t super cheme tax m ining tax s bon m rbon ss car ca intle oot der po ny Ab on lea ent To positi overnm op eral g ey lib e Hock rd Jo e Howa Jo No y Mr. rals nking Ton libe hful thi wis party ty LNP ority par min on trade l carb o protoco g Kyot sion tradin emis n credit carbo n pricing carbo ion standard emiss e change climat el sea lev atming global w elting met ice m se gas greenhou xide carbon dio on carbon emissi emissions greenhouse gas business tax big business top ten polluters UN 11

13

7

es ge ng on de els gas rgy bine rces ation policy ETS usinesnss margifits er pro Iraq nistan Afgha Sydney i Dubape o r Eu SA U x s ta fi ro t ln tax p r e a sup tion p ion tax e ac ribut ebat s t edis tax d x cut x r alth carbon ta ta dd Ru bet om nt gg C me er Gre govern inist rty or e m pa t lab prim labor rnmenent an ve m gs rali go overn ratba der t s Au n g g lea ds itio ht win ition y stan tegy l a Co rig ppos part stra d o ral bott goo libe Ab

cons

10

1 link 2 link 3 link

4

4 link

4

that the main fields of the argumentation were about politics. With a further topic, for example the one about taxations, they can be pointed out the differences between words typologies: in the pro group prevail personal name, while among cons group prevail adjectives, used to negatively characterize an unpopular tax.

6

Observing the main topic for each category it can be inferred that generally in cons’ argumentations there are a lot of comparisons with other realities deeply involved in the carbon tax controversy, because geography is the prevailing topic. In the same way, it can be observed that in the pro group the biggest topic is the one referring to the opposition party, and subsequently it can be inferred

3 1


1

0,2756675

0,31832367

0,348631 0,16664514

0,42790175

0,4922675

0,412604 0,26107815

0,26706433

0,248482

0,35867636

0,37627517

political debate

3) Which are the topics users use on support to their thesis?

0

Whilst cons comments seem to be penalized, due to their reduces semantic variability, with an observation of the relevance graph the situation seem to favour them: in all the topics the cons comments are more relevant that the pro ones, particularly in the fields of emissions, climate change and protocols. It has, though, to be underlined their lack of topics such as energies and fuels, like argumentations seem to stop at a level of criticizing the emission problem without suggesting a solution.

CONS

69,8 62,6

political debate

38,8 47,3 26,2 46,8 12,3 23,1 3,1 95,8

46


40,6 43,2 13,6 16,4 16,1 76,4 15,7 5,7 14 8,1 13,1 55,6

PRO

political debate

To finally have a general vision on the problem and to compare the word count with their relevance, it can be seen the prominence graph in which, as expected, it can be seen in a more immediate way the comparison between pro and cons and, taking in consideration a single flow, compare the single values.

47


p des pu re fic

te ion ng a a i r t t e o p t ac e v trali s d e e c d d ire tra r s d ree tics eague of Au ent f cep bel arty rnm s ure al p gove p iber rity tt L ino bbo s dy o m ny A n i To eith Sinod t come R rthur bbot A ny A ing tters Abbott To ht w ing nu paign rig ht w cam y rig ection trateg ands r el bott s arty st n leade Ab eral p ositio gs lib od opp ratba ent go ht wing overnm rig lition g t Coa ernmen abor party gov tralian l ter Aus e minis ent prim r governm labo g Combet Greg Rudd tax ts tax cu n tax debate ax carbo edistribution t walth r aln tax action p ofits tax super pr USA Europe Dubai Sydney Afghanistan Iraq super profits protit margins gas turbine business ETS IR policy carbon trading legisla tion Energy sources gas turbine clean energy Natural gas addition

si

13

ATE L DEB TICA POLI 61 words

7

6

6

3

3

3


PART 5

conclusion


part 5 - conclusion

CONCLUSION According to the graphs the controversy pattern can be summarized as follows:

67,3% CONS

17,8

14,9

PRO

NR

Among those who say yes to carbon tax, the most relevant topics are the ones related to the harmful effects of pollutants, to the political actions, and to the fossil fuels. In fact the supporters of this tax are very sensitive to environmental issues and global warming, and think that carbon tax is the first step to clean the planet from human’s pollution. Looking at the relevances of the topics of carbon tax Cons, it has been notice that people opposed to carbon tax would prefer an action about clean energy and incentives for it, rather than pay a tax that many persons can not afford. As it’s analyzed in the case study, it is interesting to see that the category Political Debate in the PRO side has a large number of words related to the opposition party, and the opposers to carbon tax have a large number of words linked to the government of Julia Gillard. Analyzing the topic Popular Reactions is easy to see the dissatisfaction related to tax and money: in many comments there examples of families who describe their economic situation and family size, and would not be able to support this tax.

50


Referring to the graph of the semantic variety, it has been noticed that in the comments PRO carbon tax this aspect hardly changes among the topics, but this that’s very different in the CONS part: the topic TAXES has a high number of words, because users of NO prefer to talk about the negativity of taxation in its varous aspects, writing a lot of impulsive and angry comments. There are many words also in the topic Majority Party, as many are the invectives against the government, Julia Gillard, and nicknames that users give to her. The category determinate (the one with words that can not be contained in any other category) is very remarkable in the topic Political Act in the YES side. Words such as “long term thinking”, “do not offer alternatives”, “better Australia”, “wealthiest countries” explain well the thoughts of users, who encourage to think to a better future of our children, and believe that a reduction of CO2 is only possible with a choice that does not offer alternatives: a political action requiring everyone to participate.

51



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