Sentiment Analysis: The top 8 and bottom 4 coins of the week

Sentiment Analysis: The top 8 and bottom 4 coins of the week

It’s as if the crypto world is collectively holding their breath.

The last few days have been good  — very, if not suspiciously good for many alts — buoyed by a pair of massive moves by Bitcoin last week. But is this a dead cat bounce on the way lower, or perhaps a more substantial rebound like we saw in April.

It’s all up to king $BTC.

And right now, the collection of 135 crypto traders and influencers I monitor for my analysis are, well, not quite ready to ring the buy bell yet.

 

The chart above shows $BTC sentiment going back to late May. The past few days have definitely shown a massive improvement over what was a pretty ugly death spiral once we broke into the $5,000s.

But few are waving the green flag just yet.  Most influencers seem to think this is a pause on our bear trend, otherwise we’d see a far more generous spike on the right side of the chart.

That doesn’t mean we may not be at the start of a larger bounce, but influencers remain wary of $BTC’s movements. Crypto’s short-term prospects likely rely heavily on $BTC’s movements over the next couple of days. Stay vigilant.

The Top Alts

This week my analysis took in more than 270,000 data points, covering 149 separate coins.  The following coins ranked highest on my “power rating,” which uses a weighted formula that combines overall sentiment, volume and the number of unique influencers mentioning a coin/token.

8.

7.

6.

5.

4.

3.

2.

1.

 

The Bottom Dwellers

These coins had some of the lowest sentiment around this week, despite nice volume.  I’ve started posting these for a different perspective, potentially showing which coins may be headed toward a bottom.

The Data

As always, here is all of the data I collected this week.

CoinSentiment (of 100)MentionsInfluencersPower Rating
ACAT251112.5
ACED935163.5
ADA50181271.25
AION472245
AKA514357
ALQO839480
AMP251112.5
APR541127
ARDR712257
ARK252234
AURA2111
BAT434248.5
BCC11115.5
BCH2512756.75
BCN42223.5
BCO92226
BIS861143
BLK251112.5
BLZ683259.25
BNB675468.75
BND866272.5
BNT11115.5
BPT251112.5
BTC455078572.5
BTCP991149.5
BURST861143
DAXT644363.5
DB683363.75
DBIX163121.25
DEV663146.25
DGB916583.5
DGD541127
DIG526255.5
DOGE854374
DRGN8181250.25
DXY4112
ELF711135.5
ENG644259
EOS46291571.25
ETC165443.25
ETH19462158.5
EVE711135.5
FOR711135.5
FOTA541127
FUN991149.5
GVT202119.5
HKN543252.25
ICX1811853.25
INS541127
IPBC861143
KEC971148.5
KLKS912155
KMD472245
LBC163233.25
LEND7016476
LINDA8521382.5
LINK24228
LOOM541127
LTC41361068
LUX434454.75
MANA251112.5
MBC712145
MONK11115.5
MSP256346.5
MWAT662142.5
NANO228551.25
NCASH02221.5
NCP546144.5
NEBL253237.75
NEO25211259.5
NEXO541127
NKN711135.5
NKTR251112.5
NOS971148.5
OCN7111577.5
ONT706674.25
OST419357.25
PCN22432159.75
PHR819581.25
PIRL252234
PIVX4112
PK434136.5
POE429459.5
POLY22222.5
POT4112
PRL941147
QKC4112
QTUM251112.5
RCN4112
REL541127
SALT251112.5
SCT862152.5
SEN525461.25
SKY714468.75
SMART972158
SNAP1110.5
SNT711135.5
SPHTX103334.75
SPX472245
SPY251112.5
SS251112.5
STR807477.5
STRAT5010566.5
SUMO252122
TEL942268.5
TFD718575.75
THETA457562.25
TKY11115.5
TOMO822262.5
TRIG711135.5
TRX53362275.5
TUBE816476.25
UUU861143
VEN8414987.25
VIA1114344
VIX0110
VOISE11115.5
VRC251112.5
WABI208448
WAN4715868.5
WAVES5410669.75
WMT251112.5
XBT108124.75
XEM711135.5
XHV251112.5
XLM644259
XLQ251112.5
XLR8318380.75
XMN952157
XMR9010484.25
XN251112.5
XP913158.75
XPTX542248.5
XRH541127
XRP23181358.25
XSN251112.5
XTL712257
XTZ206548
XVG824850.5
XZC544254
ZCL683259.25
ZEC166647.25
ZIL546462.75
ZOI951147.5
ZRX2415656

Methodology

Each week, I scrape the Twitter accounts of some of the crypto world’s favorite influencers, traders and TA folk. I run a sentiment analysis to see which coins they are mentioning positively, neutrally and which they are mentioning in a negative light.

I also take in data on unique influencers, retweets, favorites, volume and strength of feeling in sentiment.

I calculate power by through a weighted formula that takes into consideration volume, number of unique influencers and sentiment. The higher the score, the better, the lower the worse.

This isn’t financial advice, just my own way of trying to make sense of what’s out there. And as with most things, the more data I collect, hopefully, the more interesting it’ll be. This is a work in progress. Please leave suggestions on how to make it better. I imagine if I keep up with it, I’ll be able to expand a bunch of the analysis, but I wanted to start somewhere

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